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Commonly Used Statistical Tests

The following table gives you an outline of some commonly used statistical tests for a specific situation. Extensive information and concrete examples are provided in STATISTICA's help about each of these tests and procedures.

Before using any statistical test, the procedure should be researched to assure that it meets the needs of the study. Some tests make distributional and other assumptions about the data that may or may not hold. It is important to understand the analysis, hypotheses, statistical tests, and conclusions that can be drawn before performing the analysis.

What I would like to do...	My type of data...	Statistical Method
Describe one group or set of data	Interval	Basic Statistics Descriptive Statistics median, mode....
Describe one group or set of data	Ordinal	Nonparametric statistics Ordinal descriptive statistics median, mode....
Compare the mean of one group to a hypothesized population mean	Interval	Basic Statistics Difference Tests: R, %, Means t-test for Single Means
Compare 2 independent groups	Interval	Basic Statistics t-test for Independent Samples Independent t-test
Compare 2 independent groups	Ordinal	Nonparametric statistics Comparing two independent samples (groups) Wald-Wolfowitz Runs Test, Kolmogorov Smirnov Test, Mann-Whitney U Test
Compare 2 dependent groups	Interval	Basic Statistics t-test for Dependent Samples Dependent t-test
Compare 2 dependent groups	Ordinal	Nonparametric statistics Comparing two dependent samples (variables) Sign test, Wilcoxon Matched Pairs test
Compare 3 or more independent groups	Interval	Basic Statistics Breakdown & one-way ANOVA One-way ANOVA
Compare 3 or more independent groups	Ordinal	Nonparametric statistics Comparing multiple indep. samples (groups) Sign test, Wilcoxon Matched Pairs test
Compare 3 or more dependent groups	Interval	General Linear (Models)
Compare 3 or more dependent groups	Ordinal	Nonparametric statistics Comparing multiple dep. samples (variables) Friedman ANOVA, Kendall Concordance
Quantify relationship between 2 variables	Interval	Basic Statistics Correlation matrices Pearson product moment correlation
Quantify relationship between 2 variables	Ordinal	Nonparametric statistics Correlations (Spearman, Kendall tau, gamma)
Predict the value of a numeric variable from a set of predictors	Interval	Linear regression Multiple Regression General Regression Data Mining decision trees GC&RT, Interactive Trees and/or Boosted Trees Predictor Importance Data Mining, Neural Networks
Predict the nominal level of a categorical variable with 2 or more levels from a set of predictors	Nominal	Nonlinear Estimation or Generalized Linear/Nonlinear Logit regression Discriminant Analysis Data Mining decision trees GC&RT, Interactive Trees and/or Boosted Trees Predictor Importance Data Mining, Neural Networks