Category Methods

Practical guidance on research design, methodology, and data analysis for your thesis.

How to choose statistical software: R or SPSS?

Inhalt Why use statistical software for your thesis at all? R for Your Thesis: Flexible, Free – but with a Learning Curve Advantages of R Disadvantages of R Who is R suitable for? SPSS for Your Thesis: Simple, but Expensive…

The Importance of Data Management: Why It Matters More Than Complicated Analyses

Data management may sound boring at first—but anyone who takes an in-depth look at statistics for their thesis quickly realizes that it is one of the most important foundations. Even the most sophisticated analysis is of little use if the data is unstructured, flawed, or poorly documented. In this article, you’ll learn why good data management is the key to successful statistical analyses and how to do it right.

Structured workflows in R: How to write scripts efficiently

Strukturierte Arbeitsweise in R

R is one of the most powerful statistical software packages for thesis work, but many students initially feel overwhelmed by its open, script-based approach. While programs such as SPSS offer a graphical user interface for thesis work, R is based on working with code. This may sound more complicated, but in the long term it is the key to working efficiently and reproducibly. In this blog post, you’ll learn how to structure your R scripts clearly, avoid common mistakes, and optimise your analytical processes.

How to Prepare for a Statistics Exam

For many students, statistics is one of the most challenging subjects in their degree program. The exam period in particular is often associated with uncertainty, statistics anxiety, and an overwhelming amount of material. But with the right strategy, you can prepare in a focused way, close knowledge gaps, and enter the exam with a clear plan.

SPSS vs. PSPP: Which statistical software is right for your thesis?

If you need to conduct statistical analyses for your Bachelor’s or Master’s thesis, you’ll probably find it difficult to avoid using statistical software. Two of the best-known programs are SPSS and PSPP. But which software is the best choice for you? In this article, we compare SPSS vs. PSPP, show you the advantages and disadvantages of both programs, and help you make the right decision for your thesis.

Practice project: Clean Data (intermediate)

📘 Scenario You conducted a short survey with 6 statements. Three items measure everyday stress, and 3 items measure recovery behavior. Some items are negatively worded and need to be reverse-scored.The scale ranges from 1 (strongly disagree) to 8 (strongly…

Exploratory Factor Analysis in SPSS

Imagine that you have collected a large amount of survey data with 30 questions on various psychological attitudes. You suspect that only a few underlying constructs, such as "achievement motivation" or "social desirability," lie behind them. This is where exploratory factor analysis (EFA) comes in: It helps you identify a smaller number of latent dimensions from a large set of observed variables. Here, we will look at how to implement it in SPSS.

Practice project: EFA interpretation

You conducted a survey with 10 items on job satisfaction. An exploratory factor analysis (EFA) was then conducted in R. First (just to be on the safe side), a few definitions: The following R output shows the most important results:…