SPSS For Research

Course Curriculum

Chapter 1: Getting Started

Lecture 1: Introduction

Lecture 2: Course Outline

Chapter 2: The Basics

Lecture 1: Guide 1: Working With SPSS Files

Lecture 2: Guide 2: Defining Variables

Lecture 3: Guide 3: Variable Recoding

Lecture 4: Guide 4: Dummy Variables

Lecture 5: Guide 5: Selecting Cases

Lecture 6: Guide 6: File Splitting

Lecture 7: Guide 7: Data Weighting

Chapter 3: Creating Charts in SPSS

Lecture 1: Guide 8: Column Charts

Lecture 2: Guide 9: Line Charts

Lecture 3: Guide 10: Scatterplot Charts

Lecture 4: Guide 11: Boxplot Diagrams

Chapter 4: Simple Analysis Techniques

Lecture 1: Guide 12: Frequencies Procedure

Lecture 2: Guide 13: Descriptives Procedure

Lecture 3: Guide 14: Explore Procedure

Lecture 4: Guide 15: Means Procedure

Lecture 5: Guide 16: Crosstabs Procedure

Chapter 5: Assumption Checking. Data Transformations

Lecture 1: Guide 17: Checking for Normality – Numerical Methods

Lecture 2: Guide 17: Checking for Normality – Graphical Methods

Lecture 3: Guide 17: Checking for Normality – What to Do If We Do Not Have Normality?

Lecture 4: Guide 18: Detecting Outliers – Graphical Methods

Lecture 5: Guide 18: Detecting Outliers – Numerical Methods

Lecture 6: Guide 18: Detecting Outliers – How to Handle the Outliers

Lecture 7: Guide 19: Data Transformations

Chapter 6: One-Sample Tests

Lecture 1: Guide 20: One-Sample T Test – Introduction

Lecture 2: Guide 20: One-Sample T Test – Running the Procedure

Lecture 3: Guide 21: Binomial Test

Lecture 4: Guide 21: Binomial Test with Weighted Data

Lecture 5: Guide 22: Chi Square for Goodness-of-Fit

Lecture 6: Guide 22: Chi Square for Goodness-of-Fit with Weighted Data

Chapter 7: Association Tests

Lecture 1: Guide 23: Pearson Correlation – Introduction

Lecture 2: Guide 23: Pearson Correlation – Assumption Checking

Lecture 3: Guide 23: Pearson Correlation – Running the Procedure

Lecture 4: Guide 24: Spearman Correlation – Introduction

Lecture 5: Guide 24: Spearman Correlation – Running the Procedure

Lecture 6: Guide 25: Partial Correlation – Introduction

Lecture 7: Guide 25: Partial Correlation – Practical Example

Lecture 8: Guide 26: Chi Square For Association

Lecture 9: Guide 26: Chi Square For Association with Weighted Data

Lecture 10: Guide 27: Loglinear Analysis – Introduction

Lecture 11: Guide 27: Loglinear Analysis – Hierarchical Loglinear Analysis

Lecture 12: Guide 27: Loglinear Analysis – General Loglinear Analysis

Chapter 8: Tests For Mean Difference

Lecture 1: Guide 28: Independent-Sample T Test – Introduction

Lecture 2: Guide 28: Independent-Sample T Test – Assumption Testing

Lecture 3: Guide 28: Independent-Sample T Test – Results Interpretation

Lecture 4: Guide 29: Paired-Sample T Test – Introduction

Lecture 5: Guide 29: Paired-Sample T Test – Assumption Testing

Lecture 6: Guide 29: Paired-Sample T Test – Results Interpretation

Lecture 7: Guide 30: One-Way ANOVA – Introduction

Lecture 8: Guide 30: One-Way ANOVA – Assumption Testing

Lecture 9: Guide 30: One-Way ANOVA – F Test Results

Lecture 10: Guide 30: One-Way ANOVA – Multiple Comparisons

Lecture 11: Guide 31: Two-Way ANOVA – Introduction

Lecture 12: Guide 31: Two-Way ANOVA – Assumption Testing

Lecture 13: Guide 31: Two-Way ANOVA – Interaction Effect

Lecture 14: Guide 31: Two-Way ANOVA – Simple Main Effects

Lecture 15: Guide 32: Three-Way ANOVA – Introduction

Lecture 16: Guide 32: Three-Way ANOVA – Assumption Testing

Lecture 17: Guide 32: Three-Way ANOVA – Third Order Interaction

Lecture 18: Guide 32: Three-Way ANOVA – Simple Second Order Interaction

Lecture 19: Guide 32: Three-Way ANOVA – Simple Main Effects

Lecture 20: Guide 32: Three-Way ANOVA – Simple Comparisons (1)

Lecture 21: Guide 32: Three-Way ANOVA – Simple Comparisons (2)

Lecture 22: Guide 33: Multivariate ANOVA – Introduction

Lecture 23: Guide 33: Multivariate ANOVA – Assumption Checking (1)

Lecture 24: Guide 33: Multivariate ANOVA – Assumption Checking (2)

Lecture 25: Guide 33: Multivariate ANOVA – Result Interpretation

Lecture 26: Guide 34: Analysis of Covariance (ANCOVA) – Introduction

Lecture 27: Guide 34: Analysis of Covariance (ANCOVA) – Assumption Checking (1)

Lecture 28: Guide 34: Analysis of Covariance (ANCOVA) – Assumption Checking (2)

Lecture 29: Guide 34: Analysis of Covariance (ANCOVA) – Results Intepretation

Lecture 30: Guide 35: Repeated Measures ANOVA – Introduction

Lecture 31: Guide 35: Repeated Measures ANOVA – Assumption Checking

Lecture 32: Guide 35: Repeated Measures ANOVA – Results Interpretation

Lecture 33: Guide 36: Within-Within Subjects ANOVA – Introduction

Lecture 34: Guide 36: Within-Within Subjects ANOVA – Assumption Checking

Lecture 35: Guide 36: Within-Within Subjects ANOVA – Interaction

Lecture 36: Guide 36: Within-Within Subjects ANOVA – Simple Main Effects (1)

Lecture 37: Guide 36: Within-Within Subjects ANOVA – Simple Main Effects (2)

Lecture 38: Guide 36: Within-Within Subjects ANOVA – Case of Nonsignificant Interaction

Lecture 39: Guide 37: Mixed ANOVA – Introduction

Lecture 40: Guide 37: Mixed ANOVA – Assumption Checking

Lecture 41: Guide 37: Mixed ANOVA – Interaction

Lecture 42: Guide 37: Mixed ANOVA – Simple Main Effects (1)

Lecture 43: Guide 37: Mixed ANOVA – Simple Main Effects (2)

Lecture 44: Guide 37: Mixed ANOVA – Case of Nonsignificant Interaction

Lecture 45: Guide 38: Mann-Whitney Test – Introduction

Lecture 46: Guide 38: Mann-Whitney Test – Results Interpretation

Lecture 47: Guide 39: Wilcoxon and Sign Tests – Wilcoxon Test

Lecture 48: Guide 39: Wilcoxon and Sign Tests – Sign Test

Lecture 49: Guide 40: Kruskal-Wallis and Median Tests – Kruskal-Wallis Test