Topic Name Description
Course Introduction Course Syllabus
Course Textbook
1.1: Why Do We Need to Study Statistical Analysis as Part of a Business Program? Why Do We Need to Study Statistical Analysis as Part of a Business Program?
Read this article about the different ways that statistics are used in business, and why it is essential that decision-makers have the tools to analyze data as part of their skill set.
1.2: Measuring Data Definitions of Statistics, Probability, and Key Terms

This article introduces how we present a summary of data through graphs, tables, and numerical measures such as the average. This will be helpful in terms of analyzing business data in a simple way with the help of the widely-used methods in statistical analysis.

Kinds of Data in Statistics

Watch the first video from 1:03:00 to the end, and the second video until 54:00. These videos explain the foundations of statistics, what data is, and the various types of data we'll be exploring.

1.3: Measures of Spread and Data Variance and Standard Deviation

These videos explain the difference between the variance of a population of a sample, how to estimate the variance of a population based on a sample, and how to find the standard deviation and why it is important.

Descriptive Statistics

Read chapter 2, which discusses how to describe locations within a sample, and how to analyze data from a sample. Make sure you read the introduction as well as sections 2.1 through 2.7. Be sure to attempt the practice problems and homework at the end of each section.

If you would prefer to download this textbook, you may do so here.

1.4: Spreadsheet Exercises: Measures of Central Tendency and Spread Measures of Central Tendency: Mode, Median, Mean, and Midrange

This section explores the measures of central tendency: mode, median, mean and midrange. It shows you the commands for computing these metrics using a spreadsheet program and it gives you the correct format for entering those commands into the spreadsheet program.

1.5: Spreadsheet Exercises: Graphs of Histograms and Frequency Tables Graphs and Charts

Shapes of Distributions

Read this section. Note that the instructions given in the text are for version 2.x of OpenOffice. If you have 3.x, some steps are slightly different; you may need to consult the help documents.

Unit 1 Problem Set and Assessment Descriptive Statistics Homework

For this assessment, do problems 3, 5, 17, and 24–30. Some of these problems don't include solutions, so only do the ones that have solutions. To see a problem solution, click "Show Solution" beneath the problem.

2.1: Counting Terminology

Read this introduction to some of the most common formulas and terms in probability.

Counting and Probability

Watch this lecture, in which Professor Stark works through several examples of counting and probability.

2.2: Theories of Probability Independent and Mutually Exclusive Events

Read this section, which explains how to categorize the probability of an event based on what you know about the variables involved.

Venn Diagrams

This section explains some of the most common theories and formulas in probability, and demonstrates set theory by using Venn diagrams.

2.3: Set Theory Probability with Playing Cards and Venn Diagrams

Watch this video, which demonstrates how to use Venn Diagrams to understand probability.

Watch this video, which discusses Venn diagrams and the addition rule for probability.

Two Basic Rules of Probability

Read this section, which covers the symbols used in set theory. For example, the union of two sets A and B is denoted as A∩B. This section also discusses the basic rules of probability and set theory.

Set Theory

Watch these lectures, in which Professor Stark discusses set theory and works through a series of examples.

2.4: Probability Fundamentals Properties of Continuous Probability Density Functions

Read this section on the probability density function, which is the foundation for how we understand probability.

Probability Fundamentals

Watch these lectures, in which Professor Stark works through several examples of how to approach solving problems related to probability.

2.5: Probability Distributions and the Binomial Distribution Probability Density Functions and Random Variables

Watch these videos, which will introduce you to probability distributions and random variables.

Discrete Random Variables

Read this chapter, which covers the basic rules of probability and the ways that randomness affects how probabilities are distributed. Make sure you read the introduction and sections 4.1 through 4.4. Attempt the practice problems and homework at the end of each section.

Probability Distributions

Watch this lecture, in which Professor Stark works through several examples of probability distributions. The second video gives more information on how to find the mean (or expected value) of a discrete random variable.

Unit 2 Problem Set and Assessment Probability Homework

Choose ten of the problems from this set and solve them. Compare your answers against the given solutions.

Discrete Random Variables Homework

Choose ten of the problems from this set and solve them. Compare your answers against the given solutions.

3.1: The Normal Distribution Qualitative Sense of Normal Distributions

Watch this video, which gives an intuitive explanation of variables in real life that follow a normal distribution.

The Central Limit Theorem

Read this chapter, which covers some of the most important concepts used in statistics: the central limit theorem and the normal distribution. Make sure you read the introduction and sections 7.1 through 7.4. Attempt the practice problems and homework at the end of the chapter, which will give you a chance to check your understanding of these concepts.

Normal Distribution Problems: Z-score

Watch this video, which will walk you through the process of finding Z-scores, an important part of understanding this topic.

More Empirical Rule and Z-score Practice

Watch this video, will walk you through the process of solving problems using the standard normal distribution, an important part of understanding this topic.

Unit 3 Problem Set and Assessment Practice: The Normal Distribution

Complete all five exercises. You can check your work by clicking "Show Solution".

4.1: Sampling and Sampling Distributions Sampling Distribution of the Sample Mean

Watch these videos, which explain the nature of sampling distribution and how it changes as sample size changes.

Calculating the Sample Size n: Continuous and Binary Random Variables

Read this section, which explains sampling in statistics and discusses some of the possible biases when collecting data for a sample. It also explains what to consider when dealing with continuous versus binary random variables.

Sampling and Sampling Distributions

Watch the first lecture from 1:19:00 to the end, in which Professor Stark covers some problems related to sampling and sampling distributions. Then, watch the second lecture to see some additional examples.

Unit 4 Problem Set and Assessment Sampling and Data Homework

Choose 15 of these problems to solve. To see a solution, click "Show Solution" beneath the problem.

5.1: Estimation and Confidence Intervals Confidence Intervals

Read this chapter, which discusses how to construct a confidence interval for a given population. Make sure you read the introduction as well as sections 8.1 through 8.4. Attempt the practice problems and homework at the end of the chapter.

Confidence Intervals and Estimating Parameters

Watch the first lecture from 1:05:00 to the end to learn more about confidence intervals and estimating parameters. Then watch the second lecture, which goes into more detail about confidence intervals and how to use them.

Computing Confidence Intervals

Read this section to learn how to compute confidence intervals for finding a range for the real population parameter using statistics from the sample data.

5.2: Hypothesis Testing Hypothesis Testing and P-values

Watch this video, which explains how to test a hypothesis.

Hypothesis Testing with One Sample

This chapter builds on your knowledge of confidence intervals to introduce you to the concept of hypothesis testing, which is how statisticians use the scientific method to learn more about the populations they are studying. Make sure you read the introduction as well as sections 9.1 through 9.4. Attempt the practice problems and homework at the end of each section.

Hypothesis Testing

Watch the first lecture from 1:12:00 to the end. In it, Professor Stark covers problems related to hypothesis testing. Then, watch the second lecture, in which Professor Stark goes through additional problems related to hypothesis testing.

5.3: Testing Equality of Two Percentages Comparing Population Proportions

Watch these videos, which explain how to compare the proportion of two different samples.

Hypothesis Testing with Two Samples

Read this chapter, which discusses how to compare data from two similar groups. This is useful when, for example, you want to analyze things like how someone's income relates to another sample that you are interested in. Make sure you read the introduction as well as sections 10.1 through 10.6. Attempt the practice problems and homework at the end of the chapter.

5.4: The Chi-Squared Test for Goodness of Fit Introduction to the Chi-Square Distribution

Watch these videos, which introduce chi-square tests and show when each kind of chi-squared test is used.

The Chi-Square Distribution

Read this chapter, which introduces you to the three major uses of the chi-squared distribution: the goodness-of-fit test, the test of independence, and the test of a single variance. Make sure you read the introduction as well as sections 11.1 through 11.6. Attempt the practice problems and homework at the end of the chapter.

Unit 5 Problem Set and Assessment Confidence Intervals Homework

Complete the problems in the practice section. To see a solution, click "Solution" beneath the problem.

6.1 Working with More Than One Variable Linear Regression and Correlation

Read this chapter to learn how to use graphs, such as scatter plots, to analyze the relationship between two variables. Two variables may be positively or negatively related when different pairs of data show the same pattern. For example, when incomes of individuals rise so does their consumption of goods and services; thus, income and consumption are considered to be positively related. As a person's income rises, the number of bus rides this person takes falls; thus, income and bus riding are negatively related. Make sure you read the introduction as well as sections 13.1 through 13.7. Attempt the practice problems and homework at the end of the chapter.

Examples of Univariate and Multivariate Data

Watch the first lecture from 0:50:00 to the end. In it, Professor Stark differentiates between univariate and multivariate data. It also covers different data types and how to plot and interpret the correlation between data variables, and works through some examples. Then, watch the second lecture until 0:38:00, in which he works through some additional examples.

6.2: Correlation and Association The Correlation Coefficient

Read this section, which describes the formula for computing the correlation coefficient. It may be useful to save this resource for future reference to this formula. Note that the formula uses the Greek letter sigma, $\Sigma$, as the summation symbol. For instance, $\sum x_i=x_1+x_2+x_3$ when $i=1,2,3$.

6.3: Regression Linear Regression

Watch this lecture, which discusses how to interpret and understand a linear regression and how regression equations enable you to make predictions.

6.4: Spreadsheet Activity for Unit 6 Paired Data and Scatter Diagrams

Read this chapter, which discusses linear regressions and best fit lines.