Relationships and prediction
Not just "are they related" — how much, and can one predict the other.
6 modules from the SPSS & Research Methods curriculum. Covers correlation through multiple regression, logistic regression, and moderation/mediation with PROCESS.
What you'll learn
By the end of this course
- Run and interpret a correlation between two variables
- Fit a simple linear regression and interpret the slope
- Extend to multiple linear regression with several predictors
- Run a binary logistic regression when your outcome is yes/no
- Handle an ordinal or multi-category outcome with the right logistic model
- Test moderation and mediation using PROCESS
Curriculum
6 sections · 6 lessons
Section 1
6 modules
Section 1
- CorrelationWhat r measures and what it does not.~30 min
- Ordinal and multinomial logistic regressionWhen the outcome has three or more categories, and whether their order matters.~35 min
- Simple linear regressionWhat regression adds that correlation does not - a prediction and a unit.~30 min
- Moderation and mediation with PROCESSThe difference between a moderator and a mediator, with a diagram for each and a study where each is the right question.~40 min
- Binary logistic regressionWhy a yes/no outcome breaks linear regression.~40 min
- Multiple linear regressionWhat "holding the others constant" means and why it is the whole point.~40 min
About this course
Relationships and prediction is the other half of inferential statistics — where Comparing groups asks whether groups differ, this track asks how variables relate to and predict each other. It runs from a simple correlation up through full logistic regression and PROCESS-based moderation and mediation.
Six modules, about 3 hours and 35 minutes total. Correlation, simple regression, and multiple regression form one straight chain — each builds directly on the last. From multiple regression, the track splits: one path moves into binary and then ordinal/multinomial logistic regression for categorical outcomes; the other covers moderation and mediation with PROCESS.
This track assumes normality checks are already second nature, and it pulls in chi-square tests right before the logistic regression module, since that's where the two ideas meet.
Who it's for
- Anyone who's compared groups and now needs to show how variables relate or predict each other
- Researchers moving from t-tests and ANOVA toward regression-based analysis
- People who need moderation or mediation results for a thesis or paper and don't want to fumble through PROCESS alone
What you'll need
- Normality and distribution checks (Track C) completed before starting correlation
- Chi-square tests (Track D) completed before the binary logistic regression module
- Access to SPSS, including the PROCESS macro, for the final module
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