assignment business statistics

A Guide to Solving Business Statistics Assignments Effectively

Understanding the Foundations of Business Statistics for Successful Assignments

Starting a business statistics assignment can be a daunting task, especially if you're not familiar with the fundamental topics that underpin this field. Business statistics is the application of statistical methods to solve real-world business problems and make informed decisions. In this blog, we will explore the key topics you should know before diving into a business statistics assignment and provide insights on how to approach and solve these assignments effectively, potentially seeking assistance with your business statistics if needed.

1. Descriptive Statistics: The Bedrock of Analysis

Descriptive statistics forms the cornerstone of business statistics. It involves summarizing and presenting data in a meaningful way to gain insights into the data's central tendency, variability, and distribution. Before embarking on a business statistics assignment, make sure you understand the following concepts:

A Guide to Solving Business Statistics Assignments Effectively

Measures of Central Tendency: Measures of central tendency are essential statistical tools used to understand the typical value of a dataset. The mean provides the arithmetic average, the median represents the middle value, and the mode indicates the most frequently occurring value. These measures help summarize data, making it easier to gain insights and make informed decisions in business statistics.
Measures of Variability: Measures of variability are crucial in business statistics to understand the dispersion or spread of data points within a dataset. By calculating metrics like range, variance, and standard deviation, analysts can assess the degree of variation and assess the reliability of their results. These measures help businesses make informed decisions based on a comprehensive understanding of data distribution.
Graphical Representation: Graphical representation is a powerful tool in business statistics, aiding in the visualization and interpretation of complex data patterns. Histograms reveal data distributions, box plots display variability and outliers, while scatter plots illustrate relationships between variables. These visualizations enhance understanding, making it easier to communicate findings and insights to stakeholders.

2. Probability Theory: Assessing Uncertainty

Probability theory is the backbone of business statistics, enabling us to quantify uncertainty and predict outcomes. By understanding probability basics, probability distributions, and the central limit theorem, we can make informed decisions and estimate the likelihood of various business scenarios. This knowledge is invaluable in risk assessment and strategic planning. Key concepts to grasp include:

Probability Basics: Probability Basics are the foundation of business statistics, enabling us to quantify uncertainty and make informed decisions. Understanding events, sample space, and probability rules is crucial. By grasping these concepts, we can predict future outcomes, estimate risks, and assess the likelihood of various business scenarios, enhancing strategic planning and decision-making.
Probability Distributions: Probability distributions are fundamental in business statistics as they model the likelihood of different outcomes. The normal distribution is widely used due to its symmetrical shape and predictable characteristics. Binomial and Poisson distributions are valuable for discrete events. Understanding these distributions helps in making informed decisions and predicting future scenarios.
Central Limit Theorem: Central Limit Theorem is a fundamental concept in business statistics, assuring that the sample mean approximates a normal distribution, irrespective of the original data distribution. This theorem enables statisticians to draw reliable conclusions about population parameters and make accurate predictions, crucial for informed decision-making in various business scenarios.

3. Sampling Methods: Drawing Inferences from Data

Sampling methods are vital in business statistics as they allow researchers to draw meaningful inferences about a larger population from a smaller sample. Whether using simple random, stratified, or cluster sampling, understanding these techniques ensures accurate data representation and reduces the cost and time required for data collection. Before tackling assignments in this area, learn about:

Simple Random Sampling: Simple random sampling is a fundamental method in business statistics, ensuring each member of the population has an equal chance of being selected for the sample. This technique reduces bias, making the sample a representative subset of the entire population. It simplifies analysis, making it an efficient and widely used sampling method in research.
Stratified Sampling: Stratified sampling is a powerful technique in business statistics that involves dividing the population into subgroups (strata) based on certain characteristics. By ensuring proportional representation of each stratum in the sample, stratified sampling provides more accurate and reliable results, particularly when dealing with diverse or heterogeneous populations.
Cluster Sampling: Instead of sampling individuals directly, clusters of data points are randomly selected, simplifying data collection logistics. This approach helps ensure representation across different regions or groups within the population, leading to more robust conclusions.

4. Hypothesis Testing: Making Informed Decisions

Hypothesis testing is critical for making informed decisions in business statistics. By setting up null and alternative hypotheses and analyzing sample data, statisticians can determine the validity of claims and draw conclusions about population parameters. This method ensures data-driven decision-making and minimizes the risk of making incorrect judgments. Familiarize yourself with the following components:

Null and Alternative Hypotheses: Null and alternative hypotheses form the basis of hypothesis testing in business statistics. The null hypothesis states that there is no significant effect or relationship, while the alternative hypothesis asserts the opposite. By testing these hypotheses using sample data, statisticians can determine whether there is sufficient evidence to support or reject a particular claim.
Type I and Type II Errors: Type I and Type II errors are crucial concepts in hypothesis testing. A Type I error occurs when a true null hypothesis is incorrectly rejected, leading to false positives. On the other hand, a Type II error happens when a false null hypothesis is accepted, resulting in false negatives. Understanding these errors helps statisticians balance the risks when interpreting results.
p-value and Significance Level: In hypothesis testing, the p-value and significance level play crucial roles. The p-value measures the probability of observing results as extreme or more extreme than the sample data, assuming the null hypothesis is true. A smaller p-value or one below the significance level rejects the null hypothesis, indicating strong evidence for the alternative hypothesis.

5. Regression Analysis: Understanding Relationships

Regression analysis is a powerful statistical tool for understanding relationships between variables. Simple linear regression examines how one variable influences another, while multiple regression considers multiple predictors. By interpreting the coefficients, statisticians can determine the strength and direction of relationships, helping businesses make informed predictions and decisions based on data. Topics to focus on include:

Simple Linear Regression: Simple linear regression is a foundational technique in business statistics, focusing on the relationship between two continuous variables. By fitting a straight line to the data points, it quantifies the effect of one variable on another. This method allows businesses to predict outcomes based on the independent variable, aiding in forecasting and decision-making processes.
Multiple Regression: Multiple regression is a sophisticated extension of simple linear regression, allowing businesses to analyze how several independent variables impact a dependent variable simultaneously. By understanding the unique contribution of each predictor, businesses can identify the most influential factors and develop comprehensive models for more accurate predictions and strategic decision-making.
Coefficient Interpretation: In regression analysis, coefficient interpretation is crucial for understanding the impact of predictor variables on the dependent variable. Positive coefficients indicate a positive relationship, while negative coefficients imply an inverse relationship. The magnitude of the coefficient reveals the strength of the effect. Accurate interpretation ensures meaningful insights to guide business strategies and actions.

6. Time Series Analysis: Unraveling Trends

Time series analysis is essential in business statistics to identify trends and patterns over time. Seasonal decomposition separates data into its seasonal, trend, and random components. Moving averages smooth out noise and highlight underlying trends. Forecasting based on historical patterns helps businesses make proactive decisions and adapt to changing market conditions. Key concepts include:

Seasonal Decomposition: Seasonal decomposition is a vital technique in time series analysis, which separates data into seasonal, trend, and random components. By removing the seasonal effects, analysts can focus on underlying patterns and trends, enabling businesses to identify seasonal variations, make informed decisions, and plan accordingly to optimize operations and maximize profits.
Moving Averages: Moving averages are widely used in time series analysis to identify underlying trends and patterns. By calculating averages over successive subsets of data, it smoothes out fluctuations, making it easier to spot long-term trends. Businesses utilize moving averages to make predictions, detect seasonality, and inform decision-making based on historical data patterns.
Forecasting: Forecasting is a vital aspect of business statistics that aids in predicting future trends and outcomes based on historical data patterns. By employing time series analysis and other forecasting techniques, businesses can anticipate market demand, plan inventory levels, and make proactive decisions, enhancing their competitive edge and overall success.

7. Data Analysis Tools: Embrace Technology

Embracing data analysis tools like Microsoft Excel, R, and Python is essential in modern business statistics. These tools offer diverse capabilities, from basic calculations to advanced statistical modeling. Proficiency in these technologies enhances efficiency, accuracy, and the ability to tackle complex business challenges, making data-driven decision-making more effective and informed. Some widely used tools include:

Microsoft Excel: Ideal for basic statistical calculations, data visualization, and regression analysis.
Python: Another versatile programming language with various libraries for statistical analysis.

How to Solve Business Statistics Assignments Effectively

Now that you have a solid understanding of the fundamental topics, let's explore how to approach and solve business statistics assignments successfully. Solving business statistics assignments effectively requires a systematic approach. Start by comprehending the assignment's requirements, organizing data, and choosing appropriate statistical methods. Interpret results with clarity and use data visualization to enhance understanding. Seek feedback and practice regularly to build confidence in analyzing real-world business problems and making data-driven decisions.

Read the Assignment Prompt Thoroughly: Understand the requirements and expectations of the assignment before starting.
Clarify Doubts: If you're unsure about any concepts or instructions, seek clarification from your instructor or classmates.
Organize Your Data: Ensure your data is clean, organized, and ready for analysis. Use appropriate software for data manipulation.
Choose the Right Statistical Methods: Based on the nature of the data and the research question, select suitable statistical techniques.
Interpret Results: Don't merely present the numbers; explain the findings in the context of the business problem.
Double-Check Calculations: Review your calculations and statistical outputs to avoid errors.
Visualize Data: Use graphs and charts to enhance the understanding of your analysis.
Collaborate and Seek Feedback: Discuss your approach and findings with peers or instructors to gain valuable insights.
Practice Regularly: The more you practice, the more confident you'll become in applying statistical methods.
Document Your Process: Maintain a record of the steps you followed to arrive at your conclusions.

Mastering essential topics in business statistics is vital before embarking on assignments. Descriptive statistics, probability theory, and regression analysis provide the groundwork for sound data analysis. Understanding sampling methods and hypothesis testing allows for meaningful inferences and informed decisions. Equipped with the knowledge of p-values and significance levels, statisticians can confidently test hypotheses. Coefficient interpretation and graphical representation add depth to insights. Embrace data analysis tools and practice regularly to excel in your business statistics assignments, empowering you to make data-driven business decisions confidently.

The Importance of Statistics in Business (With Examples)

The field of statistics is concerned with collecting, analyzing, interpreting, and presenting data.

In a business setting, statistics is important for the following reasons:

Reason 1 : Statistics allows a business to understand consumer behavior better using descriptive statistics.

Reason 2 : Statistics allows a business to spot trends using data visualization.

Reason 3 : Statistics allows a business to understand the relationship between different variables using regression models.

Reason 4 : Statistics allows a business to segment consumers into groups using cluster analysis.

In the rest of this article, we elaborate on each of these reasons.

Reason 1: Understand Consumer Behavior Using Descriptive Statistics

Descriptive statistics are used to describe datasets.

Businesses in almost every field use descriptive statistics to gain a better understanding of how their consumers behave.

For example, a grocery store might calculate the following descriptive statistics:

The mean number of customers who come in each day.
The median sales order per customer.
The standard deviation of the age of the customers who come in the store.
The sum of the sales made each month.

Using these metrics, the store can gain a strong understanding of who their customers are and how they behave.

On the other hand, a bank might calculate the following descriptive statistics:

The percentage of customers who default on their loan.
The mean number of new customers who join the bank each day.
The sum of the total deposits made by all customers each month.

Using these metrics, the bank can get an idea of how their customers behave and how they handle their money.

Not all businesses build statistical models or perform complex calculations, but just about every business uses descriptive statistics to gain a better understanding of their customers.

Reason 2: Spot Trends Using Data Visualization

Another common way that statistics is used in business is through data visualizations such as line charts, histograms, boxplots, pie charts and other charts.

These types of charts are often used to help a business spot trends.

For example, a small business might create the following combo chart to visualize the number o f new clients and total sales they make each month:

Using this simple chart, the business can quickly see that both their sales and number of new clients tends to increase the most in the final quarter of the year.

This can allow the business to be prepared with more staff, later hours, more inventory, etc. during this time of year.

Reason 3: Understand the Relationship Between Variables Using Regression Models

Another way that statistics is used in business settings is in the form of linear regression models .

These are models that allow a business to understand the relationship between one or more predictor variables and a response variable .

For example, a grocery store might track their total amount spent on print advertising, their total amount spent on online advertising, and their total revenue.

They might then build the following multiple linear regression model:

Sales = 840.35 + 2.55(TV advertising) + 4.87(online advertising)

Here’s how to interpret the regression coefficients in this model:

For each additional dollar spent on TV advertising, the total revenue increases by $2.55 (assuming online advertising is held constant).
For each additional dollar spent on online advertising, the total revenue increases by $4.87 (assuming TV advertising is held constant).

Using this model, the grocery store can quickly see that their money is better spent on online advertising as opposed to TV advertising.

Note : In this example, we only used two predictor variables (TV advertising and online advertising), but in practice businesses often build regression models with far more predictor variables.

Reason 4: Segment Consumers into Groups Using Cluster Analysis

Another way that statistics is used in business settings is in the form of cluster analysis .

This is a machine learning technique that allows a business to group together similar people based on different attributes.

Retail companies often use clustering to identify groups of households that are similar to each other.

For example, a retail company may collect the following information on households:

Household income
Household size
Head of household Occupation
Distance from nearest urban area

They can then feed these variables into a clustering algorithm to perhaps identify the following clusters:

Cluster 1: Small family, high spenders
Cluster 2: Larger family, high spenders
Cluster 3: Small family, low spenders
Cluster 4: Large family, low spenders

The company can then send personalized advertisements or sales letters to each household based on how likely they are to respond to specific types of advertisements.

Additional Resources

The following articles explain the importance of statistics in other fields:

The Importance of Statistics in Economics The Importance of Statistics in Education The Importance of Statistics in Healthcare

Hey there. My name is Zach Bobbitt. I have a Master of Science degree in Applied Statistics and I’ve worked on machine learning algorithms for professional businesses in both healthcare and retail. I’m passionate about statistics, machine learning, and data visualization and I created Statology to be a resource for both students and teachers alike. My goal with this site is to help you learn statistics through using simple terms, plenty of real-world examples, and helpful illustrations.

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Semester Research Project in Applied Business Statistics

Julio Rivera

Department of Business

Carthage College

Rivera, J. (2015). Semester Research Project in Applied Business Statistics. Carthage College.

Description

The purpose of the assignment is to have students develop and execute a research project in applied statistics using large publicly available data sets. The work of the assignment includes hypothesis generation, data visualization, statistical testing, and analysis. In addition to writing an analytic narrative of their work, students will be required to disseminate their work by presenting it at a public poster session on campus. This assignment can be classified as undergraduate research embedded in the curriculum.

Background and Context

This assignment is for the Applied Statistics course for Business and Economics majors but could be adapted for a variety of statistics courses in other departments where large data sets are available for use. This is the semester project and the assignment requires students to demonstrate competency in the learning objectives of the course (attached with rubric). It is one of the final pieces of work that students submit during the semester and it reaches into material from the entire course. All of the expectations in the assignment are scaffolded into the course material earlier in the semester.

This assignment is designed to be an undergraduate research experience embedded into the curriculum. One of the things that my colleagues and I have learned is that research experiences need to be introduced early and integrated into the curriculum to have the maximum impact on students’ intellectual development. This assignment requires students to prepare and present a data research project that focuses on a significant business or economic question for research. This is a core experience for students before they take on larger research projects in the upper division courses.

Students most often enroll in this course during their sophomore year. Although business and economics majors dominate the room, many students throughout the institution take the course because it fulfills a general education requirement for them. Students at this level are often uncomfortable with the idea that they are responsible for designing and executing a research project that includes serious data analysis with unknown outcomes. This is why the frequent check-ins are part of the assignment design. Periodically during the semester, students are required to report progress and problems encountered in their work. Students also struggle with cutting large data sets from sites like the Census, Department of Education, IPUMS, and the Bureau of Labor statistics. Earlier assignments during the semester provide them repeated practice in navigating data sites.

Even though a statistics course is usually thought of as tied to Intellectual Skills and Quantitative Fluency, this assignment and the entire course has a deeper focus on Applied Learning and Collaborative Learning. The assignment and the course fit a model of undergraduate research embedded in the curriculum.

Alignment and Scaffolding

This is the capstone assignment for the introductory applied statistics course. It builds on students’ successfully completing assignments and tasks earlier in the semester. The assignments during the semester enable students to build the skills necessary to complete the final assignment. These assignments include learning how to cut and clean a data set so it can be analyzed, and learning how to visualize and describe data. The capstone assignment also demonstrates how an assignment about t-tests can be expanded into a semester project.

Reflections

This assignment is adapted from an assignment I used for several years when teaching Geographic Information Science (GIS). I will be using it for the first time in the applied statistics class this fall as I return to teaching after 5 years. The core of the assignment differs little from the original assignment except that, in its present form, students do not need to construct mapped results of their analysis as part of the assignment. I found this approach to be effective in getting students more deeply into the material because they had to produce a final product for their peers to inspect. As you might expect, good students do well at this assignment. However, I have found that, for the most part, marginal students do acceptable-to-good work and that they often exceed my expectations.

Students have often struggled with finding a topic. Mostly because there is just so much data out there, they get lost in the voluminous options. This is why I have included an idea sheet (with data sources). I am hoping this will help them focus a bit more. The other thing that students struggle with is envisioning what an acceptable final project might look like. I find that peppering lecture/discussion time with examples of successful past projects along with potentially successful projects is helpful.

One thing that has been helpful and you can observe in the syllabus is that the entire course is “front-loaded.” I ask more of the students early on in the semester and I “let up” on them later in the semester when they are working on their project. There is less new material in the final weeks, we more focus on discussion of how to apply what they learned early in the semester. The case study sessions that are listed on the syllabus allow me to bring in a new case study, or open it up to the students to talk about their projects and have them discuss problems or issues they may be having with the work.

It is also helpful to have an experienced student as an extra guide for students. This could be a student supplemental instructor, teaching assistant or tutor (depending on the instruction). Students will seek out their peer more often than they will seek the instructor. A good student assistant can provide information and perspective to the instructor about things that should be reviewed again in upcoming classes.

Although students use and are familiar with a whole range of technology, they are most often adept at being a consumer of technology rather than people who make technology bend to their will. This is a transition point for them. Short videos that help them use the technology are popular and useful. You can make your own or find many on YouTube.

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Chapter Review

1.1 definitions of statistics, probability, and key terms.

The mathematical theory of statistics is easier to learn when you know the language. This module presents important terms that will be used throughout the text.

1.2 Data, Sampling, and Variation in Data and Sampling

Data are individual items of information that come from a population or sample. Data may be classified as qualitative (categorical), quantitative continuous, or quantitative discrete.

Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample. Random sampling methods include simple random sampling, stratified sampling, cluster sampling, and systematic sampling. Convenience sampling is a nonrandom method of choosing a sample that often produces biased data.

Samples that contain different individuals result in different data. This is true even when the samples are well-chosen and representative of the population. When properly selected, larger samples model the population more closely than smaller samples. There are many different potential problems that can affect the reliability of a sample. Statistical data needs to be critically analyzed, not simply accepted.

1.3 Levels of Measurement

Some calculations generate numbers that are artificially precise. It is not necessary to report a value to eight decimal places when the measures that generated that value were only accurate to the nearest tenth. Round off your final answer to one more decimal place than was present in the original data. This means that if you have data measured to the nearest tenth of a unit, report the final statistic to the nearest hundredth.

In addition to rounding your answers, you can measure your data using the following four levels of measurement.

Nominal scale level: data that cannot be ordered nor can it be used in calculations
Ordinal scale level: data that can be ordered; the differences cannot be measured
Interval scale level: data with a definite ordering but no starting point; the differences can be measured, but there is no such thing as a ratio.
Ratio scale level: data with a starting point that can be ordered; the differences have meaning and ratios can be calculated.

When organizing data, it is important to know how many times a value appears. How many statistics students study five hours or more for an exam? What percent of families on our block own two pets? Frequency, relative frequency, and cumulative relative frequency are measures that answer questions like these.

1.4 Experimental Design and Ethics

A poorly designed study will not produce reliable data. There are certain key components that must be included in every experiment. To eliminate lurking variables, subjects must be assigned randomly to different treatment groups. One of the groups must act as a control group, demonstrating what happens when the active treatment is not applied. Participants in the control group receive a placebo treatment that looks exactly like the active treatments but cannot influence the response variable. To preserve the integrity of the placebo, both researchers and subjects may be blinded. When a study is designed properly, the only difference between treatment groups is the one imposed by the researcher. Therefore, when groups respond differently to different treatments, the difference must be due to the influence of the explanatory variable.

“An ethics problem arises when you are considering an action that benefits you or some cause you support, hurts or reduces benefits to others, and violates some rule.” (Andrew Gelman, “Open Data and Open Methods,” Ethics and Statistics, http://www.stat.columbia.edu/~gelman/research/published/ChanceEthics1.pdf (accessed May 1, 2013).) Ethical violations in statistics are not always easy to spot. Professional associations and federal agencies post guidelines for proper conduct. It is important that you learn basic statistical procedures so that you can recognize proper data analysis.

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Assignment on Business Statistics

What is Statistics?

Statistics is the scientific application of mathematical principles to the collection, analysis, and presentation of numerical data. Statisticians contribute to scientific enquiry by applying their mathematical and statistical knowledge to the design of surveys and experiments; the collection, processing, and analysis of data; and the interpretation of the results.

Statisticians may apply their knowledge of statistical methods to a variety of subject areas, such as biology, economics, engineering, medicine, public health, psychology, marketing, education, and sports.

Some definitions in statistics are below:

Statistic is FIBMP. It’s called “Statistic is Fiancé, Investment, Bank, Marketing, and Production.

The Croxton & Cowden are says “Statistic is COPAI”

Its mean “Statistic is collection”

“Statistic is organizing”

“Statistic is presenting”

“Statistic is Analyzing”

“Statistic is interpretation”

The Boddington says “Statistics is science of estimate”

“Statistic is science of predication”

The “Bowley says “CAM” they are “Statistic is country, Average & measurement”.

Types of statistics

There are two types of statistics.

Descriptive Statistics
Inferential Statistics

(1)Descriptive statistics

Descriptive statistics summarize the population data by describing what was observed in the sample numerically or graphically. Numerical descriptors include mean and standard deviation for continuous data types (like heights or weights), while frequency and percentage are more useful in terms of describing categorical data (like race).Descriptive statistics are as simple as the number of children in each family along a city block or as complex as the annual report released from the U.S. Treasury Department. Consider two ways of representing descriptive statistics: numerical and pictorial.

Numerical statistics

Numerical statistics are numbers, but clearly, some numbers are more meaningful than others. For example, if you are offered a purchase price of $1 for an automobile on the condition that you also buy a second automobile, the price of the second automobile would be a major consideration (its price could be $1,000,000 or only $1,000), and thus, the average—or mean—of the two prices would be the important statistic.

Pictorial statistics

Taking numerical data and presenting it in pictures or graphs is what is known as pictorial statistics. Showing data in the form of a graphic can make complex and confusing information appear more simple and straightforward.

(2) Inferential statistics

Inferential statistics uses patterns in the sample data to draw inferences about the population represented, accounting for randomness. These inferences may take the form of: answering yes/no questions about the data (hypothesis testing), estimating numerical characteristics of the data (estimation), describing associations within the data (correlation) and modeling relationships within the data (for example, using regression analysis). Inference can extend to forecasting, prediction and estimation of unobserved values either in or associated with the population being studied; it can include extrapolation and interpolation of time series or spatial data, and can also include data mining.

Levels of measurement

There are four main levels of measurement used in statistics: nominal, ordinal, interval, and ratio. Each of these has different degrees of usefulness in statistical research. Ratio measurements have both a meaningful zero value and the distances between different measurements defined; they provide the greatest flexibility in statistical methods that can be used for analyzing the data. [ Interval measurements have meaningful distances between measurements defined, but the zero value is arbitrary (as in the case with longitude and temperature measurements in Celsius or Fahrenheit). Ordinal measurements have imprecise differences between consecutive values, but have a meaningful order to those values. Nominal measurements have no meaningful rank order among values.

Because variables conforming only to nominal or ordinal measurements cannot be reasonably measured numerically, sometimes they are grouped together as categorical variables, whereas ratio and interval measurements are grouped together as quantitative or continuous variables due to their numerical nature.

Limitation on statistics in use

Actually, statistics is an exact science. It is the application of the results that leads to problems.

Perhaps the most commonly encountered limitation of statistics is the misunderstanding that a statistical measure can be used as a measure of the accuracy of a measurement.

Statistics, in general, provide very little information on the intrinsic accuracy of a measurement. Statistics can only provide an estimate of the minimal error that might be in the measurement. The actual error can be much greater than the minimal (statistical) error.

Another way to put it is that statistics measure the variability of a measurement, not the accuracy of a measurement.

Statistics is indispensable to almost all sciences – social, physical and natural. It is very often used in most of the spheres of human activity. In spite of the wide scope of the subject it has certain limitations. Some important limitations of statistics are the following:

1. Statistics does not study qualitative phenomena:

Statistics deals with facts and figures. So the quality aspect of a variable or the subjective phenomenon falls out of the scope of statistics. For example, qualities like beauty, honesty, intelligence etc. cannot be numerically expressed. So these characteristics cannot be examined statistically. This limits the scope of the subject.

2. Statistical laws are not exact:

Statistical laws are not exact as incase of natural sciences. These laws are true only on average. They hold well under certain conditions. They cannot be universally applied.So statistics has less practical utility.

3. Statistics does not study individuals:

Statistics deals with aggregate of facts. Single or isolated figures are not statistics. This is considered to be a major handicap of statistics.

4. Statistics can be misused:

Statistics is mostly a tool of analysis. Statistical techniques are used to analyze and interpret the collected information in an enquiry. As it is, statistics does not prove or disprove anything. It is just a means to an end. Statements supported by statistics are more appealing and are commonly believed. For this, statistics is often misused. Statistical methods rightly used are beneficial but if misused these become harmful. Statistical methods used by less expert hands will lead to inaccurate results. Here the fault does not lie with the subject of statistics but with the person who makes wrong use of it.

Is Statistics Science or Art?

Science refers to a systematized body of knowledge. It studies cause and effect relationship and attempts to make generalization in the form of science principles or laws.

Statistics is an art as well as a science, so it’s important to use it as you would any other tool: you have to know what you want to get out of your statistics before you can choose the right way to apply them. Therefore, let’s start with some philosophy.

First, statistics are not magic! If the data aren’t good enough, no amount of statistical manipulation will bring out the results. If your data are exceptional, the main results are often evident even without lots of massaging. Nonetheless, there are plenty of cases in the middle (where only good statistics will work), and it’s appropriate to be rigorous when possible anyway.

Second, in astronomy systematic is often a major issue. An important principle is that hypotheses are tested in bundles. When you make an observation, you aren’t measuring the physical quantities of the system directly. You make implicit assumptions about your knowledge of the instrument, and often need to make explicit assumptions about a basic model, to get the quantities that really interest you. Often there are enormous uncertainties as a result. This means that the statistical significance you quote may not be representative.

Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting numerical data for the purpose of assisting in making a more effective decision.

Art, on the other hand, refers to the skill of handling facts so as to achieve a given objective. It is concerned with ways and means of presenting and handling data making inferences logically and drawing relevant conclusions.

Statistics may thus be viewed both science and art.

Discuss on Law of Cosines

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MR. NELSON'S BUSINESS STATISTICS

Andrew Nelson of Granada Hills Charter High School Presents

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FALL 2020 STUDY MATERIALS

BUSINESS STATISTICS

AP CAPSTONE
ABM LEADERSHIP
FINAL PREPARATION
Introductions To & Overviews Of Big Data (Return Big Data Home)
Big Data Business & Finance (Return Big Data Home)
Big Data & Science (Return Big Data Home)
Big Data & Future Analytical Tools (Return Big Data Home)
Big Data, English & Art (Return Big Data Home)
Big Data & Social Sciences (Return Big Data Home)
Big Data & Education (Return Big Data Home)
Big Data, Physical Education & Medicine (Return Big Data Home)
Big Data Videos
PROJECT #1: PERSONAL HERITAGE PIZZA (PHP)
PROJECT TWO Part A: GRAPHIC DISPLAY
PROJECT TWO Part B: Graphic Display
PROJECT #3: LAYERED GRAPHIC DISPLAYS
PHD DATA NO STUDENTS SHOWN.xlsx
Drawing A Normal Distribution Curve.xlsx
PROJECT #6 PROFESSIONAL SAMPLE SURVEYS
PROJECT #8 Stock Price Rubric
FUNCTIONS OF THE REAL WORLD
MODELING TO PREDICT & EXPLAIN
STATISTICS SUPPLEMENTS
FINANCIAL LITERACY
VIDEO RESOURCES
TEXT RESOURCES
DATA RESOURCES
SYLLABUS & STATE STANDARDS

Welcome - Class Rules - Class Overview

Syllabus Download

Knowledge Matters Account Creation

Introduction To Financial Functions

Asychronous Assignments Week #1 - Due August __, 2020

Knowledge Matters Accounting Lesson #1: “ T-Accounts, Debits & Credits "

Practice Financial Functions Practice Test #A1

Practice Financial Functions Test #A1 Annotated Answers

Practice Financial Functions Test #A1 Answers PDF Format

Practice Financial Functions Practice Test #A2

Practice Financial Functions Test #A2 Annotated Answers

Practice Financial Functions Test #A2 Answers PDF Format

Asychronous Assignments Week #2 - Due August __, 2020

Knowledge Matters Accounting Lesson #2: “Using A General Journal "

Knowledge Matters Accounting Lesson #3: “The General Ledger ”

DECA DAY #1 - Chapter Elections

WEEK THREE:

Asychronous Assignments Week #3 - Due September __, 2020

Knowledge Matters Accounting Lesson #4: “Worksheet & the Accounting Cycle "

Knowledge Matters Accounting Lesson #5: “Analyzing Financial Statements ”

Asychronous Assignments Week #4 - Due September __, 2020

Knowledge Matters Accounting Lesson #6: “Managerial Accounting I "

Knowledge Matters Accounting Lesson #7: “Managerial Accounting II "

DECA DAY #2 - Chapter Campagns

WEEK FIVE:

Asychronous Assignments Week #5 - Due September __, 2020

Knowledge Matters Accounting Lesson #8: “Ratio Analysis "

Knowledge Matters Accounting Lesson #9: “Forensic Accounting Challenge I "

Asychronous Assignments Week #6 - Due September __, 2020

Knowledge Matters Accounting Lesson #10: “Forensic Accounting Challenge II "

Knowledge Matters Accounting Lesson #11: “Forensic Accounting Challenge III "

DECA DAY #3 - DECA Stock Market Game

WEEK SEVEN:

Asychronous Assignments Week #7 - Due October __, 2020

LAUNCH - GUIDED INSTRUCTIONAL PLAN

MAKE-UP FINAL EXAM & PREPARATION MATERIALS

Knowledge Matters Hotel Cumulative Assessment = Socrative Room GHCDF 2

Buy A Bond Unit Assessment = Socrative Room GHCDF 1

FINAL EXAM & PREPARATION MATERIALS

The final is comprised of two parts - Knowledge Matters Hotel Cumulative Assessment and Buy A Bond Unit Assessment . Both exams are Socrative - mostly multiple choice with some true/false. These exact questions have all been previously addressed in Zoom lectures and/or in asynchronous lesson materials. To study for the exam, go to the following Socrative rooms.

Knowledge Matters Hotel Cumulative Assessment = Socrative Room

Buy A Bond Unit Assessment = Socrative Room

Attendance at the final exam is mandatory. Students failing to take the final assessments will receive an NTI for both exams (counts as a zero in the grade calculation.) Together, these exams will account for about 5% of the student’s overall grade percentage. Students will take these exams during their live session as scheduled below. If you cannot attend class that day and/or time, please contact Mr. Nelson in advance. Expect make-up times will be scheduled between 7-8am on the remaining days of finals week.

Period Two Business Statistics Final

Wednesday June 3 - 10:30am-11:30am.

Period Three & Four Business Statistics Finals

Wednesday June 3 - 11:30am-12:30pm.

MAKE-UP Socrative Rooms Now Posted For Assignments Originally Due April 18 - May 22. Final school due date is May 29.

LinkedIn Lesson #4 = Socrative Room GHCDH3

READ Pages 18-37 From This Link Use LinkedIn To Get Into Your Dream College Then Complete Socrative Exit Survey

Career 123 Personality Test = Socrative Room GHCDH 1

Complete this career personality test 123 Career Test Then Complete Socrative Exit Survey

Knowledge Matters Hotel Simulation Lessons #8-10 plus 3 Hours Hotel Mogul Sim Active Engagement

LIVE SESSION: Wednesday, May 20 - Buy A Bond Unit Part Three

Go to Socrative Room GHCDF2 to complete the exit quiz. Note that this quiz will be retaken as part of the final exam.

Previous Class Videos For Your Review: Bond Ladders & Yield To Worst Video

Coming Soon: “We’re All Data Scientists ” Jose Andres’ GWU Graduation Address

REMOTE INSTRUCTION WEEK #9

Asynchronous Assignments: Three More Career Surveys To Complete - Note that Week #10 will be devoted to study time for the final (scheduled for June 1-5), and to completing remaining make-up work including this week’s assignments.

#1 - Complete The TypeFinder for Career Planning Assessment

Then Record Your Results in the assigned Socrative Room

Periods One & Two - SOCRATIVE ROOM GHCDP1

Periods Three & Four - SOCRATIVE ROOM GHCDP2

#2 - Complete Career Personality Profiler Assessment

Periods One & Two - SOCRATIVE ROOM GHCDP3

Periods Three & Four - SOCRATIVE ROOM GHCDP4

#3 - Complete Photo Career Quiz Assessment

Periods One & Two - SOCRATIVE ROOM GHCDF3

Periods Three & Four - SOCRATIVE ROOM GHCDF4

Please Review the GHC LATE WORK POLICY

Due May 22, 2020: Students will be able to submit work which was due between March 16 and April 17 . Students are able to earn full credit based on criteria met and successful completion of the assignment. Students are still held to the GHC Integrity Policy.

Due May 29, 2020: Students will be able to submit work due between April 20 and May 19 . Students are able to earn full credit based on criteria met and successful completion of the assignment. Students are still held to the GHC Integrity Policy.

Work assigned after May 19, 2020 must be on time for students to earn full credit based on criteria met and successful completion of the assignment.

Socrative Rooms & LinkedIn Reading Materials for Make-up - Pre-April 17: Note that Socrative room limits will require me to take these tests down after May 22. Make-up Socrative rooms for assignments given from April 20-May 19 will be posted on May 23. Socrative only provides 10 rooms per account which necessitates this rotation.

LinkedIn Lesson #1 = Must contact Mr. Nelson for exception

READ This Link LinkedIn Profile Checklist for High School Students Then Complete Socrative Exit Survey

LinkedIn Lesson #2 =Must contact Mr. Nelson for exception

READ These Two Links LinkedIn Tip Sheet - How to Communicate Effectively On LinkedIn

LinkedIn Tip Sheet - Building Your Personal Brand Then Complete Socrative Exit Survey

LinkedIn Lesson #3 = Must contact Mr. Nelson for exception

READ These Three Links LinkedIn Tip Sheet - Tailoring Your Profile To Meet Your Goals

LinkedIn Tip Sheet - How to Communicate Effectively on LinkedIn

LinkedIn Tip Sheet - Alumni Tool Then Complete Socrative Exit Survey

LIVE SESSION: Monday, May 11 - Buy A Bond Lesson - Part Two

CLASS VIDEOS: Bond Ladders & Yield To Worst Video - SOCRATIVE EXIT QUIZ

REMOTE INSTRUCTION WEEK #8

Asynchronous Assignment: Knowledge Matters “Hotel Mogul Project”

Run the Hotel Simulation for Three Hours &

Then “SUBMIT" Your Progress By Friday, May 15 11:59pm (midnight)

All will compete but who will WIN? Big Point Bonuses For The Top Performers!!

Once you have spent three hours running the Hotel Simulation, you should submit your simulation results - even if you have not reached the 85 Balanced Scorecard Goal . The Knowledge Matters softward allows teachers to see every click or lack of click you make (pretty sophisticated stuff). So please don’t try to fake it by just logging in as that will only show three hours with no activity or setting changes - that will earn no points. In addition, each of your simulation runs are saved in the system for teachers to review.

Grades will be assigned based on the following metrics.

BE ACTIVELY ENGAGED IN MAKING ADJUSTMENTS TO THE SETTINGS IN Actions>> - Many rounds of trial and error

RUN THE HOTEL SIMULATION MANY TIMES TO SEE HOW THOSE SETTING CHANGES PERFORM

Here’s a quick preview of the Hotel Simulation tasks. Refer to the lesson simulations for additional guidance on how to adjust simulation settings.

STEP ONE: In this Hotel simulation, you will manage all aspects of the hotel including:

Restaurant Operations
Banquet and Meeting Operations
Housekeeping
Group Sales Bids

Your hotel is just opening and will need to have all aspects of its operations set up. Most settings are under the "Actions” tab in the upper right hand corner of the window ( Actions>>) . If you encounter trouble setting up some elements of the hotel, don’t worry about it - just do your best for three hours, and have some fun seeing what you can get to work. YOU CAN'T BREAK IT!! GO FOR IT!!

If you find these Simulation exercises difficult, then consider setting up just the restaurant and front desk staffing first. Setting the menu pricing for the restaurant and using their scheduler tool are two of the more intuitive features. Then run the simualtion and see how you do. Again BE AGGRESSIVE at making changes.

STEP TWO: You should refer to the Actions>> " Market Data Report" to determine the characteristics of the demand for your hotel. This report includes data that can help your decision making in both your lodging operations and your food and beverage operations.

In this project, you may run the simulation for long enough to take advantage of the seasonal trends in the hotel industry. Information is as seen in the " Group Demand Seasonal Trends" graph on the Actions>> " Market Data Report" . As well, you can refer to the special events listed on the Actions>>"Front Desk" calendar month by month to determine your busy season for special events.

LIVE SESSION: Wednesday, May 6 - Buy A Bond Lesson - Part One

CLASS VIDEOS: Go to Google Classroom to view the recording of today’s lesson on purchasing bonds. No follow-up Socrative exit quiz today.

ALTERNATE ASSIGNMENT: DUE Friday, May 15 11:59PM

Instructions & Format Requirements - LinkedIn Profile Alternate Assignment

Here are the instructions for the LinkedIn Profile alternate assignment . I recorded EXT (extended time) for anyone who did not create a LinkedIn profile. Whether you requested the alternate or not, I gave you EXT so it would not negatively influence your R5 grade. Anyone with an EXT must complete the alternate assignment by Friday May 15 or the score will revert to an NTI (same as any work granted "extended time"). Let me know if you need any further direction or clarification.

LIVE SESSION: Monday, May 4

CLASS VIDEOS: Investing Basics: Bonds (3:55) AND Shedding Light on the Bond Buying Porcess - Isn’t It Time (4:40)

The exit quiz has been pulled down to open up needed Socrative rooms. Contact Mr. Nelson to arrange access.

MAKE-UP Past Missed LinkedIn Assignments (Email Mr. Nelson when done and he’ll update the grade book.)

LINKEDIN LESSON #1 - READ This Link

LinkedIn Profile Checklist for High School Students

Then complete the exit quiz. contact Mr. Nelson for SOCRATIVE ROOM.

LINKEDIN LESSON #2 - READ These Two Links

LinkedIn Tip Sheet - How to Communicate Effectively On LinkedIn

LinkedIn Tip Sheet - Building Your Personal Brand

Then complete the exit quiz. . SOCRATIVE ROOM GHCDP2 = LinkedIn Lesson #2

LINKEDIN LESSON #3 - READ These Three Links

LinkedIn Tip Sheet - Tailoring Your Profile To Meet Your Goals

LinkedIn Tip Sheet - Alumni Tool

Then complete the exit quiz. SOCRATIVE ROOM GHCDP3 = LinkedIn Lesson #3

LINKEDIN LESSON #4 - READ Use LinkedIn To Get Into Your Dream College

Pages 18-37, How to Create and Optimize Your LinkedIn Profile Items #1-7

Then complete the exit quiz. SOCRATIVE ROOM GHCDP4 = LinkedIn Lesson #4

REMOTE INSTRUCTION WEEK #7

Complete The Last Knowledge Matters Lesson

“Monitoring Competitors”

Due Friday, May 8 11:59pm (midnight)

Students Take the 123 Career Test

Then Complete A Socrative Follow-up Survey

Period Two - SOCRATIVE ROOM

Period Three - SOCRATIVE ROOM

Period Four - SOCRATIVE ROOM

FUTURE READING ASSIGNMENTS LinkedIn - From Profile to Job Seeker

LinkedIn Job Seeker Part #1

LinkedIn Job Seeker Part #2

LinkedIn Job Seeker Part #3

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PAST ASSIGNMENTS LISTED BELOW

LIVE SESSION: Wednesday, April 29

CLASS VIDEO: Can data tracking curtail the Coronavirus pandemic?

Go to Socrative Room ***** Complete Follow-up Survey For This Lesson

LIVE SESSION: Monday, April 27

CLASS VIDEO: The Computer Algorithm that was among the first to detect Coronavirus

LIVE SESSION: Wednesday, April 22

CLASS VIDEO: Mathematics of Epidemics | Trish Campbell | TEDxYouth@Frankston Bill Gates March 2015

REMOTE INSTRUCTION WEEK #6

Complete One Knowledge Matters Lesson

“Financial Reports”

Due Friday, May 1 11:59pm (midnight)

LinkedIn Lesson #5 - Students Finish Their LinkedIn Profile

Use LinkedIn To Get Into Your Dream College

R ead Pages 37-50, How to Create and Optimize Your LinkedIn Profile Items #8-16

Student Profile Due Friday, May 1 11:59pm (midnight)

REMOTE INSTRUCTION WEEK #5

Complete One Knowledge Matters Lesson

“Operations: Housekeeping”

Due Friday, April 24 11:59pm (midnight)

LinkedIn Lesson #4 - Students Begin To Create Their Own LinkedIn Profile

R ead Pages 18-37, How to Create and Optimize Your LinkedIn Profile Items #1-7

Complete Socrative Reading Quiz Due Friday April 24 11:59PM

REMOTE INSTRUCTION WEEK #4

Live Session #1 - Monday April 13, 2o2o

REVIEW - Presentation Slides April 13 Live Session

VIDEO #1 - Start Your Career - LinkedIn For Students

VIDEO #2 - LinkedIn For Students Top Five Profile To Dos

VIDEO #3 - LinkedIn Community: A Superpower Hiding in Plain Sight (Sandra Long 5/19)

SOCRATIVE ROOMS - Socrative windows will be opened 15 minutes into each session.

Period Two - Complee culminating activity in room ****

Period Three - Complee culminating activity in room ***

Period Four - Complee culminating activity in room ****

See Official GHC Schedule Below For Live Session Times - Mr. Nelson Classes

THIS WEEK’S ASYNCHRONOUS ASSIGNMENTS

Complete Two Knowledge Matters Lessons

“Operations: Restaurant & Culinary” & “Operations: Banquets & Meetings"

Both Due Friday, April 17 11:59pm (midnight)

LinkedIn Lesson #3 - Refining Your LinkedIn Profile

READ these 3 LinkedIn Reading Assignments

LinkedIn Tip Sheet - Alumni Tool

THEN PROCEED TO SOCRATIVE SELF ASSESSMENT GUIDE - Go to the appropriate Socrative room (socrative.com) and complete the multiple choice and free response questions. This assignment will be due Friday April 17 11:59pm.

LinkedIn Lesson #6 - From Profile to Job Seeker

LAUNCH - GUIDED INSTRUCTIONAL PLAN OVERVIEW

Largely A Repost of Email Sent Friday April 3

. . . The following paragraphs will share what you need to know as we prepare for a more structured schedule when school returns from spring break. Please read the entire email carefully. You need this information . The last section addresses some student inquiries regarding LinkedIn lesson #2. Try to enjoy your indoor spring breaks as much as possible, and BE SAFE! Mr. Nelson Spring Break : No change here. No work will be assigned over spring break next week. We return to school on Monday April 13. Make-up Opportunity For Work Missed In The First 3 Weeks of Remote Instruction: Given the circumstances, I am allowing all students to make-up work missed during the first three weeks of remote instruction. Knowledge Matters allows you access to these lessons at any time. Go to Socrative room 'GHCDP1' for making up the first LinkedIn lesson. For the second LinkedIn assignment, go to Socrative room 'GHCDF2’ for period two, ‘GHCDF3” for period three and ‘GHCDF4’ for period four - all will remain open over break for those students who need to make up that work. Please email me when you submit this make-up work so I know to update your grade. Quick Note To Seniors: Most of our second period are seniors, and I feel bad for you all being robbed of your grand finales in secondary education. It will give you something to tell to your grandchildren about. And know that you will tell your grandchildren about this event and your experiences living through it. As an aside (not a class requirement), I encourage you to keep a diary of thoughts as we go through the coming weeks. In some way record your thoughts to share with future generations. Trust me your memories will not be as strong when you have grandchildren (observation of an old guy). LAUNCH Guided Instructional Plan: The school will be sending "big picture" details soon but here's an outline of what Business Statistics will look like after break. Preview of Mandatory Live Instruction: Here's the big change for us. GHC will require every class to have two live class sessions of twenty minutes each; Expect these sessions will involve: (1) a five-minute welcome including a review of student protocol and student question time; (2) a lecture or video of about 10-12 minutes; and (3) a short teacher wrap-up that will provide another opportunity to ask questions. Most of the sessions will have a Socrative based follow-up assignment. That assignment will count toward the three hour asynchronous (independent) work requirement. More details on student expectations for these live sessions will be shared during break.

PLEASE NOTE THE SLIGHT CHANGE IN TIMES BELOW (This schedule aligns with the published schedule below.) Period two Buisness Statistics sessions will start at 3:00pm on Mondays and 11:00am on Wednesdays.

Period three Business Statistics sessions will start at 3:30pm on Mondays and 11:30am on Wednesdays. Period four Business Statistics sessions will start at 4:00pm on Mondays and 12:00pm (noon) on Wednesdays.

Asynchronous (aka Independent) Assignments After Spring Break: Knowledge Matters has been working well for the class. That was expected given our past experience with KM and that it's designed for remote instruction. I will continue to emphasize these highly refined materials that are designed for this form of instructional delivery. The other independent work will digest reading and video materials followed by student checks for understanding and personal reflections delivered through the Socrative platform. Let me thank everyone for your flexibility in working with the Socrative assignments so far. The Socrative based lessons were not designed to be given at home. That's a byproduct of eliminating homework from Business Statistics a few years ago. The class at large has been handling them well, and when you've encountered issues that needed clarity you've contacted me by email. Keep that up and all will continue to turn out well. The live sessions will give you an opportunity to get clarifications on future Socrative assignments (in addition to email). Due Dates: No change here. Flexibility continues to be the theme. Just continue to email me when you need additional time on any assignment or if you are unable to attend one of the live sessions. Length of Time To Complete Independent Assignments: The "asynchronous" (aka independent) instructional time of three hours will not change. Previously, I've sought to assign work that has meaning for you but does not take more than three hours per week to complete (the mandated school standard) - that has not changed. Now we all know that no assignment takes everyone the same length of time to complete. It's a good example of spread in a distribution (remember "Center, Shape, Spread & Outliers"). As the teacher, do I consider that a minimum number of hours where few spend less than three hours? Do I consider that an average number of hours where half of the students spend more than three hours and half do more than three hours? Do I consider that a maximum number of hours where nearly all students spend less than three hours? Since the school has not clarified this requirement, I have consciously decided to go with the last interpretation given the unprecedented circumstances. Excel Applications & Certification: Not everyone has equal access to Excel at home so we will not be able to pursue more on this front. That does leave some holes in what I hoped we'd cover but there is no way to fill them this semester unfortunately. For any student who wishes to pursue Excel certification when we return to school (spring or fall), we can work out timing for practice and taking the test before school or during a regular period where your teacher would let you out of class. Seniors, you would be welcome to return to campus for this purpose as well. Note On Last Socrative Assignment: Several students had inquiries about the last Socrative assignment. Here's what helped to clarify that assignment for some. Multiple choice questions are covered in the assigned reading but free response questions are reflective questions that do not have right or wrong answers. They are intended to promote you reflecting on what you might put into your LinkedIn profile. Since it's a question about you, free response "answers" would not be found in the reading itself. Do your best to address the prompt with a well thought out paragraph. Do not spend more than ten-fifteen minutes on any single free response question (some could be done in less time). If you make an honest attempt to answer, you should get all the points.

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ASSIGNMENTS - First Three Weeks of Remote Instruction

Week #3 (3/30-4/3, 2020) - Remote Learning Assignments

Greetings Business Statistics Periods 2-4 :

I hope you and your families are all safe and sound. We enter the third week of remote instruction with some clearer direction and the knowledge that we will not return to the classroom in April. Here’s the assignments for the coming week and a couple general announcements.

COMING ATTRACTION - LIVE INSTRUCTION!! The school is establishing a more structured calendar for after Spring Break that will include a live (“synchronous”) instruction component (likely two twenty-minute live class sessions per week per class). To prepare us for the live (synchronous) instruction component, I will likely schedule a class session on Google Hangout or Zoom later this week. This first session will focus on the digital logistics but it will also provide an opportunity to ask questions and get additional support. If you have suggestions on how we might best use this time together, I’m all ears. There is no precedence for what we’re doing here so all ideas are worth throwing out there.

AVAILABLE BY EMAIL EVERYDAY: Email remains the quickest and most efficient means for us to communicate. I am available most of the regular school day. If you need me to be available in real time for more interactive communication, I’ve established "office hours”. This week, you can reach to me Monday and Wednesday between 8:30-11:00pm. I’m happy to schedule appointments in other windows of time as well.

GOOGLE CLASSROOM: With us not touching base everyday, I’ve decided to post assignments on Google classroom. These instructions will be identical to those posted on the website and in the emails I send you. Refer to my email today (Monday March 30) for the Google class code.

ASSIGNMENT GRADES ARE POSTED: Grades are posted for the first two weeks of remote instruction. If you see anything that’s not right, drop me an email and it’s easily corrected. If you need an extension, just reach out and we’ll work around any limits you are encountering. If you see NTI (“not turned in”), that indicates you didn’t complete the assignment and it counts the same as a “0”. When people contact me and need additional time, I record EXT (“extended time”) until they are able to make up the work and this score designation does not impact the overall grade percentage.

WEEK #3 ASSIGNMENTS:

“Customer Service: Front Desk” & “Customer Service: Social Media Feedback"

One Due Wednesday, April 1 5:00pm & One Due Friday, April 3 5:00pm

Complete LinkedIn Lesson #2 Working With LinkedIn Profiles

Due Thursday, April 2 5:00pm

Step #1 Read the two links below then keep these sources handy to help you answer the questions in Socrative.

(Contact Mr. Nelson if you encounter any download issues.)

STEP #2 SOCRATIVE SELF ASSESSMENT GUIDE - After reading the two short PDFs above, then go to the appropriate Socrative room and complete the series of multiple choice and free response questions. This assignment will share how to build your personal brand and how to promote it on LinkedIn.

2nd Period go to Socrative Room GHCDF2

3rd Period go to Socrative Room GHCDF3

4th Period go to Socrative Room GHCDF4

Well that’s it for now. Contact me with any questions or comments. Good luck with the start of your week and be safe, Mr. Nelson

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Week #2 (3/23-27/2020) - Remote Learning Assignments

This week, you’ll complete another KM Hotel lesson ( “Marketing & Public Relations” ), but for variety I have integrated a unit on LinkedIn profiles. This unit will expose you to this important communication tool and will advance your college and career preparedness.

Complete Knowledge Matters Lesson “Marketing & Public Relations”

Due Friday, March 27 5:00pm

Complete LinkedIn Lesson #1 Introduction to LinkedIn

Due Wednesday, March 25 5:00pm

Step #1 Read LinkedIn Profile Checklist for High School Students

Contact Mr. Nelson if you encounter any download issues.

Step #2 Go the Socrative Room for your period and complete the posted REVIEW & SELF ASSESSMENT GUIDE

After reading LinkedIn Profile Checklist for High School S tudents , go to the appropriate Socrative room and complete the series of multiple choice and free response questions. This assignment will guide you through the basic layout of a LinkedIn profile, and will begin to guide you through the development of your own profile.

COMING ATRACTIONS

LinkedIn Lesson #2 Starting Your LinkedIn Profile (Future Date TBD)

LinkedIn Tip Sheets

LinkedIn Tip Sheet - Building A Great Student Profile

SOCRATIVE SELF ASSESSMENT GUIDE - After reading the two short PDFs above, then go to the appropriate Socrative room and complete the series of multiple choice and free response questions. This assignment will be due Friday April 3.

LinkedIn Lesson #3 Refining Your LinkedIn Profile (Future Date TBD)

Future LinkedIn Reading Assignments

Business Statistics

Do you want to work in the corporate world in the future? Are you a good decision maker? What do you do to enhance your business skills? Do you find business statistics work as part of testing? You should know about these types of questions if you are a student of business mathematics.

Have you ever thought about the meaning of the word “StatBusiness Statist ics’?

If not, think about it. Is it a mathematical topic or a business? If you can’t answer this question, don’t worry because it will never happen again. You will always be able to answer the question in the future with full confidence because our business accounting experts will help you learn the concept of business statistics in a very interesting way.

What Are Business Statistics?

Business Statistics refers to the use of business statistics tools such as collecting, organizing and analyzing data to make effective business operations decisions. Business statistics are important because they assist the business manager in running the business such as marketing, management, sales, accounting and more. Business statistics are a syllabus for business students. The purpose of examining students in business statistics is to develop their skills and ability to make effective decisions in their future business careers.

The Reason for Your Failure To Complete Your Business Statistics Work?

If not, take a moment to think about it. Business accounting shares for grades are part of the final marks. Students have a great deal of stress and responsibility to complete their business maths assignment and to manage their time in out-of-school activities, cultural activities, and personal activities. Lack of sufficient time to understand the subject is the main reason for failing to try the assignment.

Do you know the topics of business statistics? No! Believe it or not, but this is the answer for students. No information on business statistics is another reason for failing to complete a business statistics assignment. In such cases, most students choose business mathematical services.

Topics you can take Business Statistical Assignment Help?

Students can learn a variety of concepts in business statistics. They receive business statistics assignments that cover a wide range of topics such as:

Descriptive and absurd statistics for displaying and summarizing business data

Opportunities and random flexibility
Time series analysis
Reference numbers
The decline of simple lines
Relationships
Data mining
Tax preparation
Suggestions

Why is it necessary to take an Australian Business Statistical Help from Professionals?

Students now a day are involved in many co-curricular activities, sports and cultural communities to improve themselves. These activities enhance their continuity and increase the chances of being selected for a good job. However, knowledge and involvement in additional activities are not the only keys to a successful future, good marks in exams or exams are also required. Students fail to get good grades for many reasons such as:

The complex and complex nature of the subject makes it difficult for students to complete their assignments with high quality within a given deadline. Therefore, they are approaching the business statistics distribution services.
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Business Statistics and Analysis Specialization
The Business Statistics and Analysis Capstone is an opportunity to apply various skills developed across the four courses in the specialization to a real life data. The Capstone, in collaboration with an industry partner uses publicly available 'Housing Data' to pose various questions typically a client would pose to a data analyst.
Business statistics Full Unit notes
DMS 105 Introduction TO Business Statistics mandatory Assignment by Dr.stephen. Business statistics 100% (1) 2. Stastics 3 - Practice quiz. Business statistics 100% (1) More from: Business statistics DMS 105. KCA University. 21 Documents. Go to course. 31. Portfolio Theory , CAPM APT Students Class Notes.
Business Statistics
Now, with expert-verified solutions from Business Statistics 10th Edition, you'll learn how to solve your toughest homework problems. Our resource for Business Statistics includes answers to chapter exercises, as well as detailed information to walk you through the process step by step. With Expert Solutions for thousands of practice problems ...
Ch. 1 Introduction
The fields of economics, business, psychology, education, biology, law, computer science, police science, and early childhood development require at least one course in statistics. Included in this chapter are the basic ideas and words of probability and statistics. You will soon understand that statistics and probability work together.
BUS-352
Business Statistics (BUS-352) 1 month ago. The Wall Street Journal reported that 33% of taxpayers with adjusted gross incomes between $30,000 and $60,000 itemized deductions on their federal income tax return. The mean amount of deductions for this population of taxpayers was $16,024. Assume that the standard deviation is $2389.
OpenStax
OpenStax offers free college textbooks for all types of students, making education accessible & affordable for everyone. Browse our list of available subjects!
A Guide to Solving Business Statistics Assignments Effectively
Solving business statistics assignments effectively requires a systematic approach. Start by comprehending the assignment's requirements, organizing data, and choosing appropriate statistical methods. Interpret results with clarity and use data visualization to enhance understanding. Seek feedback and practice regularly to build confidence in ...
Preface
Introductory Business Statistics is designed to meet the scope and sequence requirements of the one-semester statistics course for business, economics, and related majors. Core statistical concepts and skills have been augmented with practical business examples, scenarios, and exercises. ... Many additional homework assignments have been added ...
The Beginner's Guide to Statistical Analysis
Table of contents. Step 1: Write your hypotheses and plan your research design. Step 2: Collect data from a sample. Step 3: Summarize your data with descriptive statistics. Step 4: Test hypotheses or make estimates with inferential statistics.
Bus 6225 B Business Statistics Individual Assignment 1 1
Bus 6225 b Business Statistics Individual Assignment 1 1 .Docx - Free download as Word Doc (.doc / .docx), PDF File (.pdf), Text File (.txt) or read online for free.
The Importance of Statistics in Business (With Examples)
The field of statistics is concerned with collecting, analyzing, interpreting, and presenting data.. In a business setting, statistics is important for the following reasons: Reason 1: Statistics allows a business to understand consumer behavior better using descriptive statistics.. Reason 2: Statistics allows a business to spot trends using data visualization.
Writing Assignments to Assess Statistical Thinking
Today's educators have expanded on possible writing assignments that may be used (Holcomb and Ruffer Citation 2000), while others have found ways to incorporate statistical writing beyond the introductory statistics course, such as in business statistics (Goenner and Snaith Citation 2003), psychology statistics (Drabick et al. Citation 2007 ...
BUSINESS STATISTIC ASSIGNMENT
BUSINESS STATISTICS SEMESTER SEPTEMBER SESI 2019/ ASSIGNMENT 1 "Current Price (RM '000) Of Randomly Selected Flat Units For A Given Size (Sq. Ft.) In Sandakan, Sabah." LECTURE'S NAME: MUHAMMAD JAFFRI BIN MOHD NASIR GROUP: L1 T Group Members Matric No. Remark(s) NUR CAHAYA BINTI OT ATOR H18A NUR IZZATI NAJWA BINTI ABDULLAH AZID H18A ROSE ...
Semester Research Project in Applied Business Statistics
This assignment is for the Applied Statistics course for Business and Economics majors but could be adapted for a variety of statistics courses in other departments where large data sets are available for use. This is the semester project and the assignment requires students to demonstrate competency in the learning objectives of the course ...
Ch. 1 Chapter Review
1.1 Definitions of Statistics, Probability, and Key Terms. The mathematical theory of statistics is easier to learn when you know the language. This module presents important terms that will be used throughout the text. 1.2 Data, Sampling, and Variation in Data and Sampling. Data are individual items of information that come from a population ...
BUSINESS STATISTICS 511 Year 1 Semester 2
Instead of using the percents, each return is represented as a multiplier indicating how much higher the value is after the year. This multiplier is 1.13 for a 13% return and 0.95 for a 5% loss. The multipliers for this example are 1.13, 1.22, 1.12, 0.95, and 0.87. The geometric mean of these multipliers is 1.05.
Assignment on Business Statistics
Some definitions in statistics are below: Statistic is FIBMP. It's called "Statistic is Fiancé, Investment, Bank, Marketing, and Production. The Croxton & Cowden are says "Statistic is COPAI". Its mean "Statistic is collection". "Statistic is organizing". "Statistic is presenting". "Statistic is Analyzing".
Business Statistics 1
Assignment 1 - Individual Case Study Analysis ECON1193 - Business Statistics 1. Student name: Samiksha Mathur Student number: s Location: RMIT Vietnam, HN Lecturer: Pham Thi Minh Thuy Class number: 1 Total pages: 7 (Excluding cover page and reference list) A. DESCRIPTIVE DATA ANALYSIS
Business Statistics
Period four Business Statistics sessions will start at 4:00pm on Mondays and 12:00pm (noon) on Wednesdays. ... Week #3 (3/30-4/3, 2020) - Remote Learning Assignments. Greetings Business Statistics Periods 2-4: I hope you and your families are all safe and sound. We enter the third week of remote instruction with some clearer direction and the ...
Assignments for Business Statistics
Assignment 14 - Introductory Business Statics | BUS 221. Data Collection and Sampling Methods - Lecture Slides | STAT 201. Solved Problems to Calculate Statistics in Regression - Homework | STAT 202. Paper Homework 2 on Introductory Business Statistics | BUS 221.
Statistics and Probability
Unit 3: Summarizing quantitative data. 0/1700 Mastery points. Measuring center in quantitative data More on mean and median Interquartile range (IQR) Variance and standard deviation of a population. Variance and standard deviation of a sample More on standard deviation Box and whisker plots Other measures of spread.
MANCOSA
For this question refer to the grouped frequency distribution shown in Table 2, in which the salaries (In R'000s) of 40 employees of a major firm are presented. The co-efficient of variation along with its interpretation is: a. 51.9% data is moderately dispersed about the mean. B. 51.9% data is highly clustered about the mean.
Business Statistics
Business Statistics refers to the use of business statistics tools such as collecting, organizing and analyzing data to make effective business operations decisions. Business statistics are important because they assist the business manager in running the business such as marketing, management, sales, accounting and more.