Applying Major Parametric Tests Using SPSS in Research
DOI:
https://doi.org/10.3126/irjmmc.v4i2.56017Keywords:
Analysis of covariance, analysis of variance, parametric tests, t-testsAbstract
This article provides a comprehensive overview of the most commonly used parametric tests, such as one sample t-test, dependent samples t-test, independent samples t-test, analysis of variance, and analysis of covariance. A parametric test is a statistical test that assumes the data being analyzed follows a certain probability distribution, typically a normal distribution. A statistical test is a procedure used in statistical analysis to make inferences about a population based on a sample of data. It covers the basics of statistical analysis, including the assumptions of parametric tests and how to check for these assumptions. It includes the access to use SPSS (Statistical Package for the Social Sciences) software to perform the tests, with detailed demonstration of outcomes and the ways of reporting them briefly. It is prepared on the basis of the secondary qualitative data garnered from journal articles, books, and web site materials. It is a valuable resource for researchers, students, and professionals who want to improve their statistical analysis skills and gain proficiency in executing analyses by using SPSS in their research in the social sciences, psychology, and other related fields.
Downloads
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Lok Raj Sharma, Sonelal Jha
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.