Courses in SPSS, Amos, Mplus, and R


I provide a number of external courses in basic and advanced statistical analysis and research methodology. For more info please contact me directly

Basics in SPSS

Introduction to SPSS                                     PDF


Content includes: Begining SPSS session, defining the variables, entering data, replacing missing values, modifying data, useful SPSS features, and screening  and cleaning the data. 


Descriptive Statistics                                     PDF


Content includes: Descriptive stats in SPSS and assessing normality


Using Graphs                                                  PDF


Content includes: Histograms, Bar graphs, Line graphs, Scatterplots, and Boxplots


Calculating Total Scores and Reliability      PDF


Content includes: Reversing negatively worded items, adding up the total scores for the scale, and checking for reliability of the scale (internal consistency)

Parametric tests

T - tests                                                          PDF


Independent samples t-test compares the mean scores of two different groups of people or conditions. Paired samples t-test compares the mean scores for the same group of people on two different occasions.


One-way between-groups ANOVA              PDF


One-way between groups analysis of variance (ANOVA) is the extension of the between groups t-test to the situation in which more than two groups are compared simultaneously.


Two-way between groups ANOVA              PDF


The two-way ANOVA compares the mean differences between groups that have been split on two independent variables (called factors). The primary purpose of a two-way ANOVA is to understand if there is an interaction between the two independent variables on the dependent variable. 


One-way repeated measures ANOVA         PDF


Repeated measures ANOVA is the equivalent of the one-way ANOVA, but for related, not independent groups, and is the extension of thedependent t-test. 


Mixed between-within subjects ANOVA    PDF


A mixed ANOVA compares the mean differences between groups that have been split on two "factors" (also known as independent variables), where one factor is a "within-subjects" factor and the other factor is a "between-subjects" factor. 


Correlation and Partial Correlation             PDF


Correlations between two variables and, partial correlation which measures the degree of association between two random variables, with the effect of a set of controlling random variables removed.


Multiple Regression                                     PDF


The general purpose of multiple regression is to look at the relationship between several independent or predictor variables and one dependent or criterion variable in one model.


Hierarchical Multiple Regression                PDF


Hierarchical regression is the practice of building successive linear regression models, each adding more predictors in blocks.


Binary Logistic Regression                         PDF


Binary Logistic regression is used to predict a categorical (dichotomous) variable from a set of predictor variables.


Multinomial Logistic Regression                PDF


Multinomial logistic regression is a classification method that generalizes logistic regression to multiclass problems. It is a model that is used to predict the probabilities of the different possible outcomes of a categorically distributed dependent variable, given a set of independent variables.

Non-parametric tests

Mann-Whitney and Kruskal-Wallis           PDF


Mann-Whitney U test is the non-parametric equivalent of the independent sample t-test. The test is sometimes known as the Wilcoxon 2-sample test. Kruskal-Wallis test is the non-paremetric equivalent of the one-way ANOVA, and an extension of the Mann-Whitney test.


Wilcoxon and Friedman                            PDF


The Wilcoxon test is the non-parametric equivalent of the the related samples t-test. The Friedman’s test is the nonparametric test equivalent to the repeated measures ANOVA, and an extension of the Wilcoxon test 


Chi-square and McNemar                          PDF


The chi-square test for independence, also called Pearson's chi-square test or the chi-square test of association, is used to discover if there is a relationship between categorical variables. Chi-square test for within-subjects designs is called McNemar's chi-square.


Advanced courses


If you are interested in advanced stats courses, please contact me for further info


I provide advanced courses in:


Structural Equation Modelling (Mplus, Amos)


Factor Analysis: Confirmatory, Exploratory, Bi-factorial solution (Mplus, Amos)


Latent Growth Modelling (Mplus, Amos)


Latent Class Analysis and mixture modelling (Mplus)


Moderation Analysis with continuous and categorical moderators (SPSS, ModGraph)


Propensity Score Analysis with matching techniques (R)


Basic and Advanced SPSS