Stats Menu Commands
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This menu contains statistical menus that can be used for analysing your data. To find out the menus that are available within each section click on the items in the list below.
Summary Statistics
Summarize Contents of Variates
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Summarize Circular Data
Diversity
Tally Table
Frequency Tables
Summaries of Groups (Tabulation)
Correlations
Statistic Tests
One and two-sample t-tests
One and two-sample binomial tests
One and two-sample Poisson tests
One-sample Nonparametric Tests
Two-sample Nonparametric Tests
Kendall's Coefficient of Concordance
Lin's Concordance Coefficient
Spearman's Rank Correlation
Kendall's Rank Correlation Coefficient
Gini Coefficient of Inequality
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Kruskal-Wallis One-way ANOVA
Friedman's Nonparametric ANOVA
Cochran's Q Test
Kappa Statistic
Gamma Statistic
McNemar's Test
Contingency Tables
Chi-Square Goodness of Fit
MANTEL Test
Distributions
Fit Distribution
Probability Plots
Kernel Density Estimation
Extremes - Maxima
Extremes - Observations above Threshold
Regression Analysis
Linear Models
Generalized Linear Models
Ordinal Regression
All Subsets Regression - Linear Models
All Subsets Regression - Generalized Linear Model
Screening Tests - Linear Models
Screening Tests - Generalized Linear Models
Split-line Regression
Standard Curves
Nonlinear Models
Generalized Linear Mixed Models
Hierarchical Generalized Linear Models
Regression Trees
Design
Generate a Standard Design
Design of Experiments
Generating factors in Standard Order
Randomizing Experimental Designs
Analysis of Variance
One and Two-way
General Analysis of Variance
Unbalanced Designs
Parallel ANOVA
Linear Mixed Models (REML)
Linear Mixed Models (REML)
Repeated Measures - Data in single variate
Repeated Measures - Data in Parallel
Multivariate Linear Mixed Models
Random Coefficient Regression
Spatial Model - Regular Grid
Spatial Model - Irregular Grid
Generalized Linear Mixed Model
Hierarchical Generalized Linear Models
Multiple Experiments/Meta Analysis
Multivariate Analysis
Principal Components Analysis
Canonical Variates Analysis
Discriminant Analysis
Principal Coordinates Analysis
Multidimensional Scaling
Hierarchical Cluster Analysis
Non-hierarchical Cluster Analysis
Procrustes Rotation
Generalized Procrustes
Correspondence Analysis
Canonical Correlations Analysis
MANOVA
Partial Least Squares
Regression Trees
Classification Trees
Six Sigma
Control Charts for Measurements
Control Charts for Attributes
Pareto Chart
Capability Statistics
Industrial Designs
Survey Analysis
Tally Table
Frequency Tables
Summaries of Groups (Tabulation)
Create Survey Weights
Modify Survey Weights
Calibration Weighting
General Survey Analysis
Single Stage Survey Analysis
Time Series
Overview of Time Series Analysis
Data Exploration (Time Series)
ARIMA Model Fitting
Spatial Statistics
Contour Plot
Surface Plot
Form Variogram
Model Variogram
Krige
Regular Grid (REML)
Irregular Grid (REML)
Setup GIS Columns
Survival Analysis
Life Table
Kaplan-Meier (Exact time points)
Kaplan-Meier (Interval based)
Nonparametric Survival Tests
Proportional Hazards
Parametric Models
Repeated Measurements
Repeated Measures - Analysis of Variance
Ante-dependence Analysis
MANOVA
Repeated Measures - Data in single variate
Repeated Measures - Data in Parallel
Generalized Estimating Equations (GEE)
Multiple Experiments
AMMI
REML Meta Analysis
Microarrays
Two Channel Microarray Design
Open Microarray Data Files
Microarray Log-Ratios
2D Plots
Histograms
Spatial Plot
One channel Quantile Normalization
Two Channel Microarray data
Estimates from Log-Ratios
Empirical Bayes Estimates
False Discovery Rate using Mixture Model
Volcano Plot
Q-Q plot
Cluster Probes/Genes
Cluster Targets/Slides
Two-way Clustering
Sample Size
t-tests
Binomial tests
Sign test
McNemar's test
Lin's Concordance
Correlations