Category Methods
Practical guidance on research design, methodology, and data analysis for your thesis.
Observation and Assessment in Diagnostics
Observation and assessment are indispensable elements of psychological diagnostics. Applying them makes it possible to analyze human behavior directly within its respective contexts, revealing specific patterns and dynamics that often remain hidden in other diagnostic procedures. In fields such as clinical psychology, educational research, and personnel selection in particular, systematic observation provides opportunities to gain deeper insights into individual behavior. This method is especially valuable when the goal is not only to collect objective data but also to understand subtle behavioral nuances that cannot be captured through tests or self-reports alone.
Data Management in SPSS
Contents Introduction Why use SPSS for data management? SPSS: Understanding the Interface and Setup The SPSS Views Syntax and Output Importing Data into SPSS Opening SPSS Files (.sav) Importing CSV/TXT Files Loading Excel files into SPSS Data preparation and transformation…
Defining the Sample and Target Population: How to Determine Whom You Should Survey
Conducting an empirical study can be quite challenging—especially if you are not exactly sure whom you should actually survey. However, defining the right sample and clearly specifying your research target population is essential to ensure that your results are meaningful. Don’t worry: in this article, you’ll get a simple step-by-step guide to determining your sample.
Exam Exercise: Hypotheses About Associations
Contents Assignment Abstract Data Collection R Script for Data Analysis R Script Output (Excerpt) Exam Questions Solution Outline Assignment Abstract The present study examined whether there is an association between daily screen time and students’ subjective perception of their sleep…
Introduction to the R package psych
The R package psych was developed by William Revelle and others to facilitate the analysis of psychological and social science data more generally. Here, we take a closer look at it.
Data Management in R
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…
Introduction to Bayesian Statistics
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…
Descriptive Statistics in SPSS
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 in R
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.
Data Visualization with SPSS
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.