Statistics 3 – ANOVA and Regression

# Statistics 3 – ANOVA and Regression

Aim of Course:

This online course, "Statistics 3 ANOVA and Regression" provides an easy introduction to ANOVA and multiple linear regression through a series of practical applications. Once you've completed this course you'll be able to correctly analyze studies with a single dependent variable and multiple independent variables. The course provides an introduction to analysis of variance (ANOVA) and multiple regression such as you might find in a year-long or four-credit college course that also included the content of our Introduction to Statistics 1 and 2 courses. This course provides a transition to more advanced or specialized courses and also a broadened perspective for anyone teaching basic statistics, especially AP Statistics.

This course may be taken individually (one-off) or as part of a certificate program.
Course Program:

## WEEK 1:   ANOVA

• One-way ANOVA
• Two-way ANOVA
• Interaction

## WEEK 2:   More on Regression; Chi-square

• Regression and interaction
• Departure from expected
• Chi-square test

## WEEK 3:  2-sample comparisons (additional topics)

• Paired comparisons
• CI for difference in means
• CI for difference in proportions

HOMEWORK:

Homework in this course consists of guided data analysis problems using software.

In addition to assigned readings, this course also has practice exercises, short narrated software demos, and supplemental readings available online.

# Statistics 3 – ANOVA and Regression

Who Should Take This Course:
Anyone who needs an introduction to ANOVA or regression, especially those interested in taking regression or more advanced courses at statistics.com.
Level:
Introductory/Intermediate
Prerequisite:
You should be familiar with introductory statistics.  Try these self tests to check your knowledge.
Organization of the Course:

This course takes place online at the Institute for 3 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Time Requirement:
About 15 hours per week, at times of  your choosing.

Options for Credit and Recognition:
Students come to the Institute for a variety of reasons. As you begin the course, you will be asked to specify your category:
1. No credit - You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
2. Certificate - You may be enrolled in PASS (Programs in Analytics and Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
3. CEUs and/or proof of completion - You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).  For those successfully completing the course,  CEU's and a record of course completion will be issued by The Institute, upon request.
4. Digital Badge - Courses evaluated by the American Council on Education have a digital badge available for successful completion of the course.
5. Other options - Statistics.com Specializations, INFORMS CAP recognition, and academic (college) credit are available for some Statistics.com courses
Course Text:

The text for this course is Introductory Statistics and Analytics: A Resampling Perspective by Peter Bruce, (2014, Wiley).   This course material will also be provided electronically, with updates, as part of the course, but you may wish to purchase the book as a reference to retain after the course is over.

Software:
In this course, software is needed for statistical analysis and simple resampling/simulation operations. We recommend one of these 4 options:
1. Regular Excel (not Excel Starter) and Box Sampler (must have Windows)
2. Regular Excel (not Excel Starter) and Resampling Stats for Excel (must have Windows)
3. StatCrunch (Windows or Mac OS)
4. R

Excel: you will need to have some facility with using formulas in Excel. If you don't, please review either this tutorial or this tutorial before the course starts.

Box Sampler: this is a free add-in for Excel, designed as a visual teaching and learning tool for doing resampling simulations. Runs only on Windows.  Installation file is here, documentation here.

Resampling Stats for Excel: this is a commercial add-in for Excel, designed as a practitioner's tool for doing resampling simulations. A free license is available to all course participants, while they are enrolled in the statistics.com sequence of introductory statistics courses. Runs only on Windows. Enrolled students will be given access to a free 1-year trial of Resampling Stats through the software download link on the main Stats course webpage.  You can also visit the Resampling Stats website and download the 1-year trial here.

StatCrunch: this is a very affordable web-based statistical software program, which also has simulation and resampling capabilities. Runs over the web, so can be used with both Windows and Mac. Resampling is not as intuitive as with Box Sampler and Resampling Stats for Excel.  Learn more at www.statcrunch.com.

NOTE for StatCrunch Users:  On all platforms, we recommend that you use the New version of StatCrunch.  All examples in the textbook supplement are based on the New version of StatCrunch.

R: R is a powerful opensource statistical scripting language that is widely recognized as an industry standard.  You will need to have familiarity with R and RStudio prior to taking the Statistics 1, 2 or 3 courses if you choose to use R as your software package.  Comprehensive supplemental materials are available for R users.  You can learn more about R here and RStudio here.

Instructor(s):

Dates:

July 12, 2019 to August 02, 2019 September 13, 2019 to October 04, 2019 November 15, 2019 to December 06, 2019

# Statistics 3 – ANOVA and Regression

Instructor(s):

Dates:
July 12, 2019 to August 02, 2019 September 13, 2019 to October 04, 2019 November 15, 2019 to December 06, 2019

Course Fee: \$399

Do you meet course prerequisites? What about book & software? (Click here to learn more)

We have flexible policies to transfer to another course, or withdraw if necessary (modest fee applies)

Group rates: Click here to get information on group rates.

First time student or academic? Click here for an introductory offer on select courses. Academic affiliation?  You may be eligible for a discount at checkout.

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