The JASP Guide's purpose is to assist the novice social science and education researcher in interpreting statistical output data using the JASP Statistical Analysis application. Or, I could say that this guide helps you understand quantitative analysis without the tears. Through the examples and guidance, you will be able to select the statistical test that is appropriate for your data, apply the inferential test to your data, and interpret a statistical test's results table. The Guide goes into the uses of some of the most common statistical tests and discusses some of the limitations of those tests, i.e. Chi-square using Contingency Tables (Test of Independence), t-Test (Independent, Paired, and One Sample), One-Way ANOVA, Correlation, Point Biserial Correlation, and Regression (Simple and Multiple Linear). Exploratory Factor Analysis (EFA) and Principal Component Analysis (PCA) have been included in this guide as a valuable procedure in data reduction. The focus of this guide will be the typical statistical analysis tools that may be useful for the novice or beginning researcher.

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Medium erhältlich in:
2 MSH Medical School Hamburg, Hamburg
2 MSH Medical School Hamburg, Hamburg

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Personen: Halter, Cristopher P.

Schlagwörter: Statistik Datenanalyse Regression Software t-Test Varianzanalyse Forschungsmethoden JASP Open-Source