Get started with R
Go from being a beginner to being able to perform your own analyses
Choose between instructor-led online training in SPSS or R.
Theory is mixed with examples and exercises to help you get started with both the software and the fundamentals of statistics in the best way possible.
Statistikakademin is the Nordic region’s leading company in statistical software training. We have around five hundred participants in our courses every year with extremely high overall ratings. We constantly hear from participants that they consider our courses to be a perfect introduction to the field of statistics. The overwhelming majority of them are employed as PhD students, researchers, or analysts.
SPSS 1
Data and graph management with Basic statistics
December 13–14, on Zoom
Content
• Data management
• Describing data with tables and graphs
• Basic statistical concepts
• Correlations
• Comparisons of mean values
• Tables and relationships between categorical variables
• Non-parametric methods
R 1
Introduction to R, Linear regression, and ANOVA
November 15–16, on Zoom
Content
• Handling data
• Data visualisation
• Correlations
• T-test
• Linear regression
• Modern statistical tests
• Linear regression
• ANOVA
R 2
Advanced regression, Survival analysis & Visualisation
December 6–7, on Zoom
Content
• Logistic regression
• Poisson regression
• Kaplan-Meier curves
• Cox PH regression
• Log rank test
• Visualisation
• Exploratory data analysis
• The ggplot2 package
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News and updates
Go from being a beginner to being able to perform your own analyses
Start using R and learn how to handle the statistical methods you need to work independently with your own analyses.
Data and graph management with Basic statistics in SPSS
What are the benefits?
Let us help you raise the quality of your work this fall.
• Introduction to modern statistics • Cluster analysis & SEM
Courses in R & SPSS
Rehearse old knowledge or learn something new at our educatons this fall
A short Q&A with the course developer Måns Thulin
Learn how to visually explore data in R.