Go to a section on this page: Descriptive statistics, testing distributions, comparison tests, nonparametric comparison tests, comparing regression lines, frequency and contingency tables, variance tests, survival analysis, exploratory data analysis, fitting models to data.
Descriptive statistics (sample size, number missing, mean, median, standard deviation, etc.)
Testing distributional goodness of fit (normality tests, Kolmogorov-Smirnov test, chi-square goodness of fit test)
Testing equality of means or location (t test, analysis of variance [ANOVA], sign test [one-sample and two-sample paired], signed rank test [one-sample and two-sample paired], rank sum test, Kruskal-Wallis test, Friedman's test, Compare Samples, Cochran's Q test, McNemar's Q test)
Nonparametric comparison tests:
Nonparametric tests of location or spread (sign test [one-sample and two-sample paired], signed rank test [one-sample and two-sample paired], rank sum test, Kruskal-Wallis test, Friedman's test, Compare Samples, Cochran's Q test, McNemar's Q test, Ansari-Bradley test)
Comparing simple linear (straight-line) regression lines (analysis of covariance [ANCOVA])
Frequency and contingency tables:
Frequency and contingency tables (categorical analysis) (creating frequency tables, cross-tabulation [creating contingency tables, measures of association], contingency table analysis [chi-square test for independence, Fisher's exact test])
Testing equality of variances or dispersions (chi-square test for variance, F test, Levene's test, Bartlett's test, Ansari-Bradley test)
Survival analysis (analyzing and comparing survival functions) (life tables, Kaplan-Meier plot, comparing survival curves [Mantel-Cox test, Gehan-Breslow test, Tarone-Ware test])
Model fitting (simple linear (fitting a line: b0 + b1*x),
multiple linear (fitting a linear combination of x terms: b0 + b1*x1 + b2*x2 + ... + bn*xn),
polynomial (fitting a polynomial, b0 + b1*x + b2*x**2 + ... + bn*x**n),
non-linear (fitting an arbitrary function f(x), e.g., (vmax*x) / (km+x),
dose*exp(-k*t)),
logistic (fitting the logit of y by a linear combination of x terms:
b0 + b1*x1 + b2*x2 + ... + bn*xn))
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