The Introductory Statistics Courses

The Institute offers a full sequence of introductory courses in statistics, plus a single course that is a survey of basic topics. These courses have been developed and taught by leading authorities on teaching statistics with the needs of the introductory student in mind. Our goal is real understanding, not cookbook learning, and even the most anxious novice (as well as the expert!) will benefit from our rich array of courses that provide a bit of repetition and overlap, as well as multiple perspectives on a sometimes difficult topic.


Credit
The American Council on Education (ACE) has approved two of these courses, Statistics 1 and Statistics 2 (together they constitute the equivalent of an undergraduate introductory course in statistics), as part of its "credit recommendation service." Learn how it works here. If you enroll with ACE, you will receive marks on homework and a scheduled final exam (learn more about the exam process here). If you pass both Statistics 1 and Statistics 2, you will receive a transcript from the Institute, via ACE.  Note that whether an introductory statistics course is accepted for credit at a given institution is the decision of that institution.


If you do not need academic credit, but still need to show that you took these courses, you can obtain a "Record of Completion" directly from the Institute. Records of completion confer "continuing education credits" (CEU´s), not academic credit. They require successfully completing the course (which includes the homework, but not a final exam - the final exam is required only if you are seeking academic credit via ACE).

NOTE: the introductory courses may not be taken out of sequence, or simultaneously, for any reason.

 

The Introductory Course Sequence - begins every month

Statistics 1 - Probability and Study Design and Statistics 2 - Inference and Association:

Taken together, these two courses provide the equivalent of an undergraduate semester course in statistics. The American Council on Education (ACE) has reviewed these two courses and recommends that they be recognized as the equivalent of a 3 credit undergraduate course in statistics. This is part of the "credit recommendation service" of ACE; click here for instructions on obtaining academic credit. 

Prerequisite: None
Placement test (optional):  click here if you have taken statistics before and think you don't need to start at the beginning.
Who should take these courses: You should take these courses if you require the equivalent of an undergraduate course in introductory statistics, or if you are planning to take additional courses at The Institute.

Statistics 3 - ANOVA and Regression:

This course covers ANOVA and multiple linear regression. This course should be taken by anyone planning to progress to additional Statistics.com courses.
Prerequisite: You should be familiar with the material covered in Statistics 1 and Statistics 2.
Placement test (optional): click here if you have taken statistics before and think you don't need to start at the beginning.
Who should take this course: You should take this course if you are moving onto more advanced Statistics.com courses. This course is also suited to anyone who has been drafted into teaching an introductory statistics course without much background in statistics.

 

More Introductory Courses

Introduction to Resampling:

Inferential statistics (hypothesis testing and confidence intervals) is, at its core, all about the behavior of samples drawn from larger, hypothetical populations. This course approaches this often confusing subject from an entirely empirical and user-friendly perspective: take lots of samples (by computer) and see how they behave.
Prerequisite: None
Who should take this course: Students learning statistics who want an understanding and appreciation of hypothesis tests and confidence intervals that is both deeper and easier-to-understand than that gained from a traditional formula approach

Designing Valid Statistical Studies:
This online course, "Designing Valid Statistical Studies" covers the issues that need to be addressed in order for a study to produce statistically valid conclusions.   We mainly deal with statistical study designs that are not experiments, and are used with observational data.  We use examples mainly from the epidemiology literature, which is where the methodology of observational studies has been used and developed, but the principles apply to any study based on observational data.
Prerequisite: While not strictly required, we recommend taking the Institute's introductory statistics sequence first, as this will enable you to continue with additional Institute courses directly upon completing this course.    The mathematics level in this course is basic algebra.
Who should take this course: Researchers who need to design, or review the designs of, statistical studies.

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