Course Syllabus

Welcome to MA121: Introduction to Statistics. General information about this course and its requirements can be found below.

Course Designer: Ou Zhao, Ph.D., University of Michigan

Course Description: Examination of the properties behind the basic concepts of probability and statistics, designed to teach you ways to investigate the relationships between various characteristics of data.

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 ACE Alternative Credit ProjectTM. 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. You will also need to download and install the Wolfram CDF Player™ in order to complete the various interactive labs used throughout the course.

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.

For additional technical guidance check out Saylor's tech-FAQ and the Moodle LMS tutorial.


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.

StraighterLine Introduction to Statistics Exam

This course is designed to align with StraighterLine's Introduction to Statistics examination. Visit the StraighterLine website, to view the syllabus for their MAT202 course.  For more information about this partnership, and earning credit via StraighterLine exams, go here


Thomas Edison State University TECEP Exam

It also aligns with a Thomas Edison State University TECEP examination. Visit the TECEP website, and click on "Principles of Statistics (STA-201-TE)” to download the content guide for the exam.  For more information about this partnership, and earning credit through Thomas Edison State University, go here.

    Thomas Edison State University

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 92.5 hours to complete this course. Each 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 (a total of 4.75 hours) on Monday and Tuesday nights; subunit 1.2.1 (a total of 4.75 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. You may access the discussion forums at

It will be helpful to have a calculator for this course. If you do not own one or have access to one, consider using this free version.

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

Learning Outcomes

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

  • define and apply the meaning of descriptive statistics and statistical inference, describe the importance of statistics, and interpret examples of statistics in a professional context;
  • distinguish between a population and a sample;
  • calculate and explain the purpose of measures of location, variability, and skewness;
  • apply simple principles of probability;
  • compute probabilities related to both discrete and continuous random variables;
  • identify and analyze sampling distributions for statistical inferences;
  • identify and analyze confidence intervals for means and proportions;
  • compare and analyze data sets using descriptive statistics, parameter estimation, hypothesis testing;
  • explain how the central limit theorem applies in inference, and use the theorem to construct confidence intervals;
  • calculate and interpret confidence intervals for one population average and one population proportion;
  • differentiate between type I and type II errors;
  • conduct and interpret hypothesis tests;
  • identify and evaluate relationships between two variables using simple linear regression; and
  • discuss concepts pertaining to linear regression, and use regression equations to make predictions.
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

Last modified: Thursday, August 18, 2016, 10:12 AM