Statistics & Data Analysis
Agreement about statistical method
Data cleaning (ETL)
Analysis and visualisation
Results interpretation
Hypothesis Testing
Applying appropriate statistical testing
Parametric tests (t-test, ANOVA, ANCOVA)
Non-parametric tests (Wilcoxon Signed-Rank, Mann-Whitney U, Kruskal-Wallis, Friedman and Sign Test)
Prediction
Using parametric and non-parametric tests for prediction
Pearson correlation, linear regression, logistic regression, multivariate regression
Spearman correlation, chi-square
Instrument Validation
Using tests to determine reliability, validity, sensitivity and objectivity
Internal Consistency Reliability (Cronbach α)
Construct Validity (Factor Analysis) and convergent validity (correlation with other measures of the same construct)
Floor and Ceiling Effects
Inter-Rater Reliability
Structural Modeling
Using advanced statistics to answer more complex hypothesis
Factor Analysis
Structural Equation Modeling