Testing a hypothesis (polystohastic approach; p value, CI, effect size, bayesian statistics (BF))
Parametric and non-parametric tests
Robust test
Variety of sampling distribution - testing
Univariate and multivariate methods
Linear and non linear correlation (zero order, first order...)
Mediation and moderation (SEM); full mediation, partial mediation, recursive and non recursive, CFA, EFA
Path analysis
Log-linear (qualitative data);
T-test, ANOVA (one-way, two-way;n way; factorial; post hoc), MANOVA, Discriminative analysis, Canonical
correlation (CCA),
Bayesian inference (posterior probability); Bias
Posterior probability
ANCOVA - Analysis of covariance (general linear model)
MANCOVA - Multivariate Analysis of covariance (n way)
Bootstrapping procedures (re sampling by iteration)
Tranformation data - X3 (cube),X2 (square),(square root),X0 (?log), reciprocal root, reciprocal,reciprocal square
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Descriptive - MCT (mean, mode, median), MV (variance, standard deviation, Coefficient of variation, skewness, kurtosis, IQ, quantile...
Contingency tables
Data visualization - graphs, bars. charts, Q-Q plots, P-P plots, Box and plots, histograms, scatter, residual plots
Logit and probit regression, laso mad ridge regresion (L1 regularization,
L2 regularization)
Ridge regression, quantile regression, Multinomial logistic regression; logit, probit....
MACHINE LEARNING - Neural Networks (CNN, GNN, RNN...)
Kernel regression
Cox regression (Kaplan Meier)