Course Syllabus

Welcome to BUS204: Business Statistics. General information about this course and its requirements can be found below.

Course Designer: David T. Bourgeois, PhD, and Bharatendra K. Rai, PhD

Course Description: Introductory survey of quantitative methods (QM), or the application of statistics in the workplace. Examines techniques for gathering, analyzing, and interpreting data in any number of fields—from anthropology to hedge fund management. 

Getting Started

After familiarizing yourself with the following course syllabus, enroll in this course using the “Enroll me in this course” button located on the left hand toolbar. Once enrolled, navigate to Unit 1 of the course to read the Unit Introduction and Unit 1 Learning Outcomes. Links and instructions for all unit specific course resources will follow the introductory materials.

Earning College Credit

This course provides students the opportunity to earn actual college credit. It has been reviewed and recommended for 3 credit hours by The National College Credit Recommendation Service (NCCRS). While credit is not guaranteed at all schools, we have partnered with a number of schools who have expressed their willingness to accept transfer of credits earned through Saylor. You can read more about our Saylor Direct Credit program here.

Evaluation and Minimum Passing Scores

In order to pass this course, you will need to earn a 70% or higher on the final exam. Your score on the exam will be tabulated as soon as you complete it. If you do not pass the exam on your first attempt, you may take it again as many times as needed, following a 7-day waiting period between each attempt. 

You will only receive an official grade on your final exam. However, in order to adequately prepare for this exam, we recommend that you work through the materials in each unit. Throughout the course you may find practice quizzes or other assignments that will help you master material and gauge your learning. Scores on these assignments are informational only and do not contribute to your overall course grade. 

If you are seeking to earn college credit, you must take and pass the Saylor Direct Credit final exam. That exam will be password protected and require the presence of a proctor.

Technical Requirements

This course is delivered fully online. You will be required to have access to a computer or web-capable mobile device and have consistent access to the internet to either view or download the necessary course resources and to attempt any auto-graded course assessments and the final exam.

To access the full course including assessments and the final exam, you will need to be logged into your Saylor Academy account and enrolled in the course. If you do not already have an account, you may create one, free of charge, here. Although you can access some course resources without being logged into your account, it’s advised that you login to maximize your course experience. For example, some of the accessibility and progress tracking features are only available when you are logged in.  

If you plan to attempt the optional credit recommended final exam that accompanies this course, then you will also need access to a webcam enabled computer. A webcam is needed so that our remote proctoring service can verify your identity, which will allow Saylor Academy to issue an official transcript to schools on your behalf. Full details about remote proctoring for credit recommended exams can be found here

Embedded throughout the text are the SticiGui Java applets. Think of these applets as little software programs that you can use to explore the different aspects of statistics you are learning. The minimum system requirements for using the SticiGui exercises and the Java applets are detailed hereThese applets should be compatible will all major browsers; Java needs to be enabled in order for them to work.

For additional technical guidance check out Saylor’s tech-FAQ and the 



There is no cost to access and enroll in this course. All required course resources linked throughout the course, including textbooks, videos, webpages, activities, etc are accessible for no charge. This course also contains a free final exam and course completion certificate.

This courses does contain an optional final exam that will provide students an opportunity to earn college credit. Access to the exam itself is free, though it does require the use of a proctoring service for identity verification purposes. The cost for proctoring is $25 per session.

Time Commitment

While learning styles can vary considerably and any particular student will take more or less time to learn or read, we estimate that the "average" student will take 122.25 hours to complete this course. Each overall unit, resource, and activity within the course is similarly tagged with an estimated time advisory. We recommend that you work through the course at a pace that is comfortable for you and allows you to make regular (daily, or at least weekly) progress. It's a good idea to also schedule your study time in advance and try as best as you can to stick to that schedule.

It may be useful to take a look at these time advisories, to determine how much time you have over the next few weeks to complete each unit, and then to set goals for yourself. Perhaps you can sit down with your calendar and decide to complete Subunit 1.1 and Subunit 1.2 (total of 4.75 hours) on Monday and Tuesday nights; Subunit 1.3 (a total of 5.5 hours) on Wednesday and Thursday nights; etc.


Learning new material can be challenging, so below we've compiled a few suggested study strategies to help you succeed. 

Take notes on the various terms, practices, and theories as you read. This can help you differentiate and contextualize concepts and later provide you with a refresher as you study.

As you progress through the materials, take time to test yourself on what you have retained and how well you understand the the concepts. The process of reflection is important for creating a memory of the materials you learn; it will increase the probability that you ultimately retain the information.

Although you may work through this course completely independently, you may find it helpful to connect with other Saylor students through the discussion forums or study groups. You may access the discussion forums at

This course uses a complete online textbook, developed by Dr. Philip Stark at the University of California, Berkeley. This textbook is used in Dr. Stark's Business Statistics course. This textbook includes several interactive examples that you can use to enhance your learning. Do not skip these examples! Learn how they work and try to understand them. Many times, Dr. Stark will use these examples in the online video lectures, so be sure to watch for them and work the examples as he works them in class. You can read what the author of the materials has to say about the best way to use these materials by reviewing the material in the Preface.

Special Instructions on SticiGui exercises and Java applets: Every chapter in the online textbook has exercises to check your understanding; you should carefully work through each exercise. The author of the text has provided instructions on how to work with the exercises here: SticiGui: "How to Use These Materials.”

Each Java applet has instructions posted next to it in the text. You can find a listing of all the SticiGui Java applets here; follow the links to each applet for further description and instructions on how to use each one. 

Pay special attention to Unit 1, as it will lay the ground work for understanding the more advanced, explanatory material presented in the latter units.

The relationship between the book chapters and the video lectures is listed below. Please note the different lecture numbers depending upon if you access them via YouTube or iTunes U.

YouTubeiTunes USticiGui Chapters Covered
Lecture 1Lecture 1Intro to class, Chapter 1 (0:00 to 57:28)
Lecture 2Lecture 2Chapter 3 (1:03:00 to 1:16:08)
Lecture 3Lecture 3Chapter 3 (0:00 to 54:00),
Chapter 4 (54:00 to 1:14:23)
Lecture 4Lecture 4Chapter 4 (0:00 to 50:00),
Chapter 5 (50:00 to 1:16:12)
Lecture 5Lecture 5Chapter 5 (0:00 to 38:00),
Chapter 7 (41:00 to 1:18:57)
Lecture 6Lecture 6Chapter 9 (3:50 to 57:50),
Chapter 11 (57:50 to 1:11:48)
Lecture 7Lecture 7Chapter 11 (0:00 to 47:00),
Lecture 8Lecture 8Chapter 12 (0:00 to 1:16:41)
Lecture 9Lecture 10Chapter 13 (0:00 to 1:15:02)
Lecture 11Lecture 14Chapter 14 (0:00 to 1:20:52)
Lecture 12Lecture 15Chapter 17 (0:00 to 1:20:59)
Lecture 13Lecture 16Chapter 17 (0:00 to 1:23:41)
Lecture 14Lecture 17Chapter 17 (0:00 to 56:00),
Chapter 18 (56:00 to 1:25:13)
Lecture 15Lecture 18Chapter 19 (0:00 to 1:21:08)
Lecture 16Lecture 19Chapter 20 (0:00 to 1:25:21)
Lecture 17Lecture 20Chapter 21 (0:00 to 1:24:52)
Lecture 18Lecture 21Chapter 22 (0:00 to 1:20:42)
Lecture 19Lecture 22Chapter 23 (0:00 to 1:19:00),
Chapter 24 (1:19:00 to 1:23:45)
Lecture 20Lecture 23Chapter 24 (0:00 to 1:19:31)
Lecture 21Lecture 24Chapter 25 (0:00 to 1:05:00),
Chapter 26 (1:05:00 to 1:18:42)
Lecture 22Lecture 25Chapter 26 (0:00 to 1:12:00),
Chapter 27 (1:12:00 to 1:20:03)
Lecture 23Lecture 26Chapter 27 (0:00 to 1:20:57)
Lecture 25Lecture 29Review of semester
Note: There are no lectures for chapters 15, 16, 29, and 30. 

Learning Outcomes

Upon successful completion of this course, you will be able to:

  • explain the importance of statistics to business;
  • explain the differences between quantitative and qualitative data, and identify examples of each type of data;
  • define and apply the following terms: data sets, mean, median, mode, standard deviation, and variance;
  • summarize and interpret data in a tabular format using frequency distributions and visually with histograms;
  • define and apply the concept of a probability distribution, and explain the properties of different distributions;
  • differentiate between discrete and continuous probability distributions;
  • define and apply the concept of a random variable, and differentiate the population from a sample;
  • relate the central limit theorem to sample size and normal distribution;
  • describe and identify the different sampling methods, including systematic, stratified random, cluster, convenience, panel, and quota sampling, and identify examples of each;
  • use a point estimator from a sample to estimate the entire population;
  • estimate intervals over which the population parameter could exist using sample data;
  • apply hypothesis testing for testing population parameters using one or two samples;
  • identify the dependent and independent variables in the linear regression model;
  • plot a regression line, and explain how the regression coefficient shapes that line; and
  • work with statistical data in a spreadsheet environment.

Throughout this course, you'll also see related learning outcomes identified in each unit. You can use the learning outcomes to help organize your learning and gauge your progress.

Suggested Prerequisites

In order to take this course, you should:

  • have read the Saylor Student Handbook; and
  • have confirmed that your browser meets the minimum requirements laid out for the online textbook;
  • have access to a calculator that includes the ability to do square roots. (A statistical calculator is available as part of the online textbook we are using here. You may also use the calculator that comes with your operating system, which should have square root capability if you set it to the proper mode.);
  • have completed either MA001: Beginning Algebra or MA005: Calculus I, or the equivalent; and
  • have completed the following courses (optional):
    • BUS103: Introduction to Financial Accounting
    • BUS105: Managerial Accounting
    • ECON101: Principles of Microeconomics
    • ECON102: Principles of Macroeconomics
    • BUS202: Principles of Finance, and
    • BUS203: Principles of Marketing

Last modified: Wednesday, 28 October 2015, 5:05 PM