Inhalt Introduction Grundlagen & Setup Important Packages RStudio-Projekte & Verzeichnisse Reading in Data Reading in CSV/TXT Files Reading in Excel Files Other Formats Data Preparation and Transformation Basic Operations with dplyr Examples of Transformations Filtering and Sorting Variable Coding Handling…
Inhalt Why Bayesian Statistics? Differences Between Frequentist and Bayesian Statistics Example: Medical Test Bayes’ Theorem Meaning of the Terms: Visual Example: A Manipulated Coin? Conjugate Priors Example: Binomial Distribution with a Beta Prior Credible Intervals R Code for Illustration Why…
SPSS is one of the most widely used programs for statistical data analysis. One of its basic functions is calculating descriptive statistics to analyze central tendencies and measures of dispersion. In this article, I will show you how to calculate the mean, median, standard deviation, and other statistics in SPSS.
Exploratory factor analysis (EFA) is one of the most important techniques in psychology and the social sciences for identifying latent constructs in data. It helps you understand the structure of questionnaires or tests and eliminate irrelevant items. In this blog post, I will show you how to conduct an EFA in R, including data preparation, factor extraction, rotation, and interpretation of the results. We will also explore the methodological background and present further examples of applications in various research fields.
The graphical presentation of data is an important part of data analysis. SPSS offers various ways to prepare data visually, including bar charts, histograms, boxplots, and scatterplots. In this article, I’ll show you how to create and interpret visualizations in 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…
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.
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.
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.
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.