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 firstname.lastname@example.org.
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)
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.
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.
If you are interested in advanced stats courses, please contact me for further info email@example.com
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