-Surveys development and data analysis
-Descriptive statistics: Cross tabulation, Frequencies, Descriptives, Explore, Descriptive Ratio Statistics.
-Bi-variate statistics: Means, t-test, ANOVA, Correlation (bi-variate, partial, distances),Nonparametric tests.
-Prediction for numerical outcomes: Linear regression
-Prediction for identifying groups: Factor analysis, cluster analysis (two-step, K-means, hierarchical), Discriminant
-Analytics, Business intelligence,Data mining, Exploratory data analysis,Multi-way data analysis.
-Statistical inference:Statistical theory ,Frequentest inference, Point estimation, Interval estimation, Testing hypotheses, Parametric tests, Specific tests, Goodness of fit, Rank statistics, Bayesian inference
-Multivariate :Regression Anova Principal components Canonical correlation Discriminant analysis Cluster analysis Classification Structural equation model Factor analysis
-Design of Experiments (DOE)
-100% Pass Pearson exams, assignments, and discussions