Pearson and Spearman Correlation – Interpretation of Results

Correlation analysis is a fundamental statistical method used to examine relationships between two variables. The most commonly used coefficients are the Pearson correlation coefficient (r) and the Spearman rank correlation coefficient (ρ).

Both coefficients range from -1 to +1, where the sign indicates direction and the magnitude indicates the strength of the relationship (Mukaka, 2012).

Regression Analysis in SPSS – How to Interpret Results

Regression analysis is one of the most widely used statistical methods in scientific research, including bachelor’s, master’s, and doctoral theses. Its main purpose is to examine the relationship between a dependent variable and one or more independent variables.

This guide explains how to interpret regression results in SPSS, focusing on key output tables and their meaning.

Statistical Guides – SPSS, AMOS and Data Analysis

Statistical data analysis is a fundamental component of modern scientific and business research. Without proper application of statistical methods and correct interpretation of results, reliable conclusions cannot be achieved.

Central Limit Theorem and the Use of Parametric and Nonparametric Statistics: Data Normality and Large Sample Requirements

1. Introduction

The Central Limit Theorem (CLT) is a fundamental principle of inferential statistics. It enables the use of parametric statistical tests even when the raw data are not perfectly normally distributed.