Statistics / Data Analysis in SPSS: Factorial ANOVA
4.8 (97 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
1,185 students enrolled

Statistics / Data Analysis in SPSS: Factorial ANOVA

Applied data analysis in SPSS, covering the one-way ANOVA, two-way ANOVA (main effects and interaction), and more!
4.8 (97 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
1,185 students enrolled
Last updated 9/2014
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This course includes
  • 3 hours on-demand video
  • 12 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • learn how to interpret the one-way ANOVA between and within subjects designs
  • Learn how to run and interpret a two-way ANOVA, including main effects and interactions
  • learn how to conduct simple effects tests on the interaction effect
  • understand the source table in ANOVA, including the relationship between SS, MS, df, and F
  • Learn about effect sizes, include eta-square and partial eta-square
  • gain much greater facility in SPSS
  • Have fun doing it in a learn at your own pace, non threatening format!
Requirements
  • Introduction to statistics course (either currently taking or already have completed)
  • Access to IBM SPSS Software (strongly recommended)
Description

November, 2019.

This course covers - step by step - a number of different ANOVAs and related statistical tests in SPSS. The following important statistical procedures are covered in the course:

1) One-way between ANOVA 

2) One-way within ANOVA

3) Post-hoc tests

4) Two-way between ANOVA (main effects, interaction effect, and simple effects)

5) Introduction to a three-way ANOVA

In completing this course, you will:

  • Learn how to write the results of statistical analyses in a professional "best practices" format.

  • Learn how to quickly recognize and interpret the most important information in statistical output.

  • Substantially increase your confidence in this highly respected subject matter. 

  • Increase your marketable quantitative job skills.

  • Learn how to use a common program for conducting statistical analyses: SPSS.

Designed by a award-winning (in teaching) statistics professor with a focus on both simple and accurate step-by-step explanations of the material. Substantially increase your knowledge of analysis of variance and inferential statistics -- enroll today!

Who this course is for:
  • Students seeking help with SPSS, especially how to analyze and interpret the results of ANOVA tests
  • Professionals desiring to augment their statistical skills
  • Anyone seeking to increase their data analytic skills
Course content
Expand all 19 lectures 03:13:23
+ Course Introduction
1 lecture 02:50

An overview of the course is provided in this lecture.

Note: The SPSS data files for the entire course are located in the lecture 2 folder.

Preview 02:50
+ One-Way Between Subjects ANOVA
4 lectures 36:31

Note: The SPSS data files for the entire course are located here.

In this lecture, the one-way between subjects ANOVA is covered.

Learning Tip: The one-way between subjects ANOVA may be used when 2 or more separate or unrelated groups are compared. Many people think of this test being used with 3 or more groups, but it is fine to use it for two groups as well. (Either the ANOVA or the independent samples t test can be used when there are two unrelated groups).

One-Way Between Subjects ANOVA
10:13

Learning Tip: "Post-hoc" means "after the fact"; post-hoc tests are typically conducted after a significant result is found for the ANOVA. If the ANOVA is not significant, then post-hoc tests typically are not interpreted.

While there are many different post-hoc tests available, Tukey's test is covered here as (1) it is one of the more commonly used post-hoc tests and (2) research has shown that Tukey's test does a good job at keeping the overall alpha level at .05.

Note: The output for the post hoc test was provided in the prior lecture.

One-Way Between Subjects ANOVA - Post Hoc Tests
10:13

The various part of the source table are covered in this video, including SS, MS, F, and df. How the MS is equal to a variance and how F = variance between/variance within is also discussed.

Source Table Explained
09:27

Eta-square, the measure of effect size for the one-way between subjects ANOVA is covered here. Eta-square is equal to Sum of Squares (SS) between groups/Sum of Squares (SS) Total.

Cohen's standards for eta-square are .01 = small, .06 = medium, and .14 = large.

Measure of Effect Size - Eta-Squared
06:38
+ One-Way Within Subjects ANOVA
2 lectures 23:35

In this lecture, the one-way within subjects ANOVA is covered.

Learning Tip: The one-way within subjects ANOVA may be used when 2 or more dependent or related groups are compared. Many people think of this test being used with 3 or more groups, but it is fine to use it for two groups as well. (Either the within ANOVA or the dependent samples t test can be used when there are two related groups).

One-Way Within Subects ANOVA
11:14

In this lecture, post-hoc tests are covered. The appropriate post-hoc test to use for the within subjects ANOVA is the dependent samples t test, with a separate t test used for each pair of groups.

Note: The output for the post hoc test was provided in the prior lecture.

One-Way Within Subjects ANOVA - Post Hoc Tests
12:21
+ Two-Way Between Subjects ANOVA
5 lectures 01:09:00

In this video, the first part of a two-way ANOVA is covered here, including the background for an ANOVA and how to produce the output in SPSS.

Note: The SPSS data file for this lecture is located in lecture 2 as a zip file. (All data files for the course are in the lecture 2 folder.)

Two-Way Between Subjects ANOVA - Part 1
11:23

Part 2 of the two-way ANOVA is covered here, with a focus on interpreting the results that are output in SPSS.

Two-Way Between Subjects ANOVA - Part 2
16:23

The interaction effect is covered in this video. Interaction indicates that the lines are significantly non-parallel (for a profile plot in SPSS), which means that the impact of one factor differs across the levels of the other factor.

Displaying the Interaction Effect - Profile Plots and Bar Charts
12:56

Simple effects are covered in this video, with all four possible simple effects tested. Simple effects test one factor at a single level of the other factor.

Preview 14:13

How to set up the data file in SPSS is covered here for the two-way ANOVA, which is an important topic and often an area of confusion where mistakes in structuring the data file are often made.

Data Entry Example
14:05
+ One-Between One-Within ANOVA
5 lectures 55:04

Part 1 of the one-between one-within ANOVA.

One-Between One-Within ANOVA - Part 1
17:41

Part 2 of the one-between one-within ANOVA.

One-Between One-Within ANOVA - Part 2
09:31

In this video, we take a look at the interaction effect for the one-between one-within ANOVA.

One-Between One-WIthin ANOVA - Interaction Effect (Part 3)
10:35

In this video, we illustrate how to conduct simple effects tests on the interaction effects in the one-between one-within ANOVA (part 1 of 2).

Simple Effects Tests - One-between One-Within ANOVA (Part 1)
09:24

In this video, we illustrate how to conduct simple effects tests on the interaction effects in the one-between one-within ANOVA (part 2 of 2).

Simple Effects Tests - One-between One-Within ANOVA (Part 2)
07:53
+ Three-Way ANOVA - Overview
1 lecture 05:33

An overview of a 3-way between subjects ANOVA is provided in this video. The different effects that are tested (A, B, C, A x B, A x C, B x C, and A x B x C) and a description of the 3-way interaction (A x B x C) are covered.

Three-Way ANOVA - Overview
05:33
+ Conclusion
1 lecture 00:50

A conclusion to the course is provided here. Congratulations to all who completed the course! Great job!!

Conclusion
00:50