Category Thesis

Scenario:You are investigating whether a motivation workshop significantly increases employees’ motivation. To do this, motivation is measured before and after the workshop. Dataset: Mittel_Motivationsvergleich.csv Download data Variables: Solution in R 1. Import the data daten <- read.csv("Mittel_Motivationsvergleich.csv") 2. Check the…

If you have data from the same people at two points in time – e.g., before and after training – you need the paired-samples t-test in SPSS. This test examines whether the two measurements differ significantly. It is typically used for pre-post measurements, but also for measurements involving pairs or twin studies.

Scenario:You collect data from people in three groups (e.g., professional fields) on their interest in technology using three items. Examine whether Group 1 and Group 2 differ significantly in their scale mean. Group 3 should not be taken into account.…

You already know what an analysis of variance (ANOVA) is and when to use it. Now it’s time to put it into practice: You’ll get a complete workflow for conducting a one-way ANOVA in R—including assumption tests, model specification, post-hoc tests, and visualizations.

Inhalt Example: Study Methods and Exam Performance 1. Entering Data in SPSS 2. Checking the Assumptions a) Normality (Shapiro–Wilk test) b) Homogeneity of variances (Levene’s test) c) Independence 3. Conducting a One-Way ANOVA Example Output: Descriptive Statistics Test of Homogeneity…

Inhalt Example: Mindfulness Training and Stress 1. Entering data in SPSS 2. Conducting a Repeated Measures ANOVA a) Defining the factor b) Assigning the measurement time points c) Setting the options 3. Interpreting the results a) Mauchly’s test of sphericity…

One-Way ANOVA is great when you want to examine the influence of one factor on a numerical outcome variable. But what if you have two—and want to know whether they jointly or even interactively influence the outcome?

Then you need a Two-Way ANOVA, also called factorial ANOVA.

In this exercise, you’ll learn how to use a one-way analysis of variance (ANOVA) in R to test whether average job satisfaction differs significantly between three departments. You’ll prepare the data manually, check the assumptions of ANOVA, and conduct the analysis, including a Tukey post hoc test. This practical exercise will help you apply statistical methods to real-world questions in a targeted way.

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…