Courses on Applied Statistics
Course number 415
Regression and ANOVA with SPSS
In research it is often important to model the influence of several continuous or categorical variables on a single,
dependent response variable. Models constructed can be used to help understanding the underlying process or to make
response predictions possible for specific designs or situations. Statistical data analysis techniques for building
linear regression models and ANOVA models may be valuable for this.
In the CEE/e-course ‘Regression and ANOVA with SPSS’ standard techniques for linear regression and ANOVA model
building are discussed. Attention is paid on the interpretation of the results and on the practical use of the
models for prediction. Furthermore, the use of representative statistical software like SPSS is demonstrated and
participants get the opportunity for hands-on experience using SPSS for linear regression and ANOVA.
The following topics will be treated:
• Introduction and Overview.
• Exploratory Data Analysis: Scatter Plots,
Correlations and Partial Correlations.
• Building, Evaluating and Using Linear Regression Models.
• One-way and Factorial Analysis of Variance (ANOVA),
Main Effects and Interactions.
• Post-hoc Tests, Contrasts and Model Evaluations.
• Nonparametric Tests: Kruskall Wallis.
• Interpretation and Presentation of the Results.
After successful completion of the course participants should be able to build linear regression and ANOVA models with SPSS independently.
||Will be handed out at the beginning of the course.
||The language of communication can be either Dutch or English, to be
decided by mutual arrangement with the participants.
||Basic knowledge Applied Statistics (testing & estimation), as treated in a.o.
the CEE/e-course "Applied Data Analysis with SPSS"
||Partly theory, partly hand-on experience.
This course is not yet scheduled.
|Number of participants
||minimum: 10, maximum: 20
||The course is also available on request.
The course is part of the CEE/e-certificate program
"Statistical Modeling and Data Analysis with SPSS"