
Continuous
 Sum, Mean, Variance, SD, CV%, Skewness, Kurtosis
 Geometric Mean, Harmonic Mean new in v4.50
 Median, Minimum, Maximum, Range, IQR
 Quantiles
 Mode
 Histogram with optional normal overlay
 Frequency polygon
 Dot plot – jittered, aligned, spread points and vary point symbol/color
 Skeletal box plot, Tukey outlier box plot, Quantile box plot
 Mean error bar plot, Mean confidence diamond plot
 CDF plot with optional KolmogorovSmirnov confidence band
 Normal QQ plot with optional Lilliefors confidence band
 ShapiroWilk, AndersonDarling, and KolmogorovSmirnov tests for normality
 Z test for mean with known population SD
 Student’s one sample ttest for mean
 Wilcoxon test for mean/median
 Sign test for median
 X2 test for variance
 Mean estimate with tbased or Zbased confidence interval
 Median with ThompsonSavur confidence interval
 HodgesLehmann pseudomedian with Tukey confidence interval
 Variance with X2based confidence interval

Discrete
 Frequency table – frequency, cumulative frequency, relative frequency, cumulative relative frequency
 Frequency bar plot with optional cumulative frequency line
 Frequency pie plot
 Binomial exact test for proportions
 Score Z test for binomial proportions
 Pearson X2 and Likelihood ratio G2 test for multinomial proportions
 Proportion with ClopperPearson exact or Wilson score confidence interval


 Descriptive statistics by group
 Sidebyside dot plots, mean plots, box plots by group
 Z test for difference in means with known population SDs
 Student’s independent samples ttest for difference between means
 Welch’s ttest for difference between means with unequal variances
 WilcoxonMannWhitney test for difference between means/medians
 1way betweensubjects ANOVA for equality of means
 Welch’s ANOVA for equality of means with unequal variances
 KruskalWallis test for equality of mean/medians
 Mean difference with tbased, WelchSatterthwaite tbased, or Zbased confidence interval

 Cohen’s and Hedge’s g standardized mean difference with noncentral tbased confidence interval
 HodgesLehmann location shift with Moses confidence interval
 Multiple comparisons procedures: Student’s t (individual comparisons), TukeyKramer (all pairs), Dunnett (against control), Hsu (with best), Scheffe (all contrasts), Steel (nonparametric against control), DwassSteelCritchlowFligner (nonparametric all pairs), Wilcoxon (nonparametric individual comparisons)
 MeanMean scatter plot for multiple comparisons
 Ftest for variance ratio
 Bartlett, Levene, and BrownForsythe tests for homogeneity of variances


 Descriptive statistics for each group
 Sidebyside dot plots, mean plots, box plots by group
 Difference plot with identity line and optional histogram of differences
 Ztest for difference in means with known population SDs
 Student’s paired samples ttest for difference between means
 Wilcoxon signed ranks test for difference between means/medians
 Sign test for difference between medians

 1way withinsubject ANOVA for equality of means
 Friedman test for equality of medians
 Mean difference with tbased or Zbased confidence interval
 Cohen’s and Hedge’s g standardized mean difference with noncentral tbased confidence interval
 Median difference with ThompsonSavur confidence interval
 HodgesLehmann location shift with Tukey confidence interval


 Contingency table
 Grouped frequency plot
 Stacked frequency plot
 Pearson X2 test for independence / equality of proportions
 Likelihood ratio G2 test for independence
 Mosaic plot for association with color by category or residual
2x2 related tables
 McNemarMosteller exact test for symmetry / marginal homogeneity
 Score Z test for difference between proportions
 Proportion difference (risk difference) with Newcombe score or Tango score confidence interval
 Odds ratio with Binomial exact or Wilson score confidence interval

2x2 tables
 Fisher exact test for independence
 Score Z test for difference between proportions
 Proportion difference (risk difference) with MiettinenNurminen score, Newcombe score, or Tango score confidence interval
 Proportion ratio (risk ratio) with MiettinenNurminen score or Newcombe confidence interval
 Odds ratio with Hypergeometric exact or MiettinenNurminen score confidence interval


Linear Fits
 Simple linear regression
 Polynomial regression (2nd to 6th order)
 Logarithmic regression
 Exponential regression
 Power regression
 Multiple linear regression
 ANOVA new in v4.80
 ANCOVA new in v4.80
 Advanced models with simple, crossed, polynomial and factorial terms, with categorical explanatory variables coded as dummy variables
Other Fits
 Binary logistic regression

 Model equation
 Summary of fit – R2, AIC, BIC
 Parameter estimates – beta, confidence intervals, VIF, standardized beta
 Scatter plot with fit line and optional confidence bands
 Ftest effect of model
 Predicted against actual plot
 Ftest effect of each term in model
 Leverage plot for effect of each term
 Residual plot – raw, standardized
 Sequence and Lag1 plots
 Outlier and Influence plot
 Cook's D influence
 Predict Y for X
 Effect means for categorical variables new in v4.80
 Main effect and interaction plots for categorical variables new in v4.80
 Multiple comparisons of effect means: Student’s t (individual comparisons), TukeyKramer (all pairs), Dunnett (against control), Hsu (with best), Scheffe (all contrasts) new in v4.80
 Ftest for lack of fit test for simple regression models
 Save model variables back to the dataset: Fitted Y, Residuals, Standardized Residuals, Studentized Residuals, Leverage, Cook's Influence

Multivariate

 Correlation matrix with color map on coefficients
 Covariance matrix
 Scatter plot
 Scatter plot matrix
 Vary points by color of based on a factor
 Pearson r correlation coefficient with Fisher’s Z confidence interval
 Pearson test for linear association
 Spearman rs correlation coefficient with Fisher’s Z confidence interval
 Kendall tau correlation coefficient with SamaraRandles confidence interval
 Kendall test for monotonic association
 Cronbach’s alpha (standardized and unstandardized)
 Deleted Cronbach’s alpha for each item

 Eigenvalues / Eigenvectors
 Coefficient matrix with color map to reveal relationships
 Classic Gabriel biplot with variables as vectors and observations as points
 GowerHand biplot with variables and observations as points
 Predict new observations / variables
 Reflect, rotate, and scale biplot
 Correlation monoplot to show relationship between variables
 Scree plot
 Maximum likelihood factor extraction
 Factor pattern / structure matrices with color map to reveal structure
 12 factor orthogonal/oblique rotations including Varimax, Oblimin
