Data Analysis case study

# Methods to consider to solve the case study

1. Hypothesis development and testing (both parametric and non-parametric)

2. t-test, levene test, Kolmogorov-smirov and shapiro-wilk, cohen's d, post-hoc power analyis

3. Mann-whitney U test, Wilcoxon

3. Anova (oneway, two-way, ancova), F-test, welch test, priori contrast, post-hoc tests (Games-Howell, tukey HSD, Hochberg GT2), omega-squared, interaction (hybrid, ordinal, disordinal)

4. linear regression (Normality, Homoscedasticity, No autocorrelation, No omitted variables, No multicollinearity, reliable data) P-P plot, K-S, S-W tests, Condition-index, Variance Inflation Factor, outliers (fit, factor), Measures for the Identification of Outliers, leverage, studentized deleted residuals, cook's distance, DFFITS, DFBETAS, Covratio, cross-validation, dummy variable regression

5. Common factor analysis and Principal component analysis, Kaiser-Meyer-Olkin, Anti-image correlation matrix, Bartlett's test of sphericity, eigen-value, commonality, factor loadings, kaiser criterion, scree plot, parallel analysis, factor rotation (oblimin, promax)

Note: How can I add dataset PaperMill.sav file to analyze in the SPSS