You examine whether the average stress level differs significantly between male and female participants. Using a t-test (and, if appropriate, a Mann–Whitney U test), you learn how to turn a research question into a testable hypothesis—and how to test it in R or SPSS.
Inhalt Task Case description R script Output Questions Interpretation of the output Theoretical and methodological foundations Reflection and application Sample solution Interpretation of the output Theoretical and methodological foundations Reflection and application Task Case description The aim of this study…
Inhalt Task description Case description Information about data collection R script with data analysis R output (excerpt) Exam questions Sample solution Task description Case description An experimental study examined whether a four-week mindfulness training improves students’ stress management skills. Three…
Inhalt Simple Regression Multiple Linear Regression Interactions (Moderation Multicollinearity Common Pitfalls R Commands at a Glance Mini-Project: mtcars Data Conclusion Imagine you want to estimate your exam grade based on a single number, e.g. study time in hours. Or perhaps…
In this exercise, either on your own or in a group, you will carry out a small practice project that requires applying content from the basic chapters on descriptive statistics.
Exploratory factor analysis is a powerful tool that helps you identify hidden patterns in large datasets. Imagine you are trying to find out which personality traits in a group of people are related to one another. Rather than letting the complexity overwhelm you, EFA allows you to structure the data in a way that helps you formulate clear hypotheses and gain exciting insights.
This exercise is designed to help you practice working with multiple data sets that have inconsistent names, merging and cleaning them, and then processing them further—both in R and SPSS.
Inhalt Learning objectives Overview of the task Data description Step-by-step guide Solutions Solution in R Solution in SPSS Summary Learning objectives By the end of this exercise, you should be able to: Overview of the task You have a dataset…
This article is about descriptive statistics and visualization in R. R is a free and incredibly versatile programming language that gives you everything you need not only to analyze data statically, but also to visualize it impressively.
Inhalt Simple chart types Histogram Box plot Bar chart (barplot) Scatter plot Plot customizations Exporting graphics Conclusion R has always included a package of graphics functions, so you do not need to install anything extra. These “Base Graphics” are: These…