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
- Summary Statistics
- Summary of Circular Data
- Diversity
- Tally Table
- Frequency Tables
- Summary Tables
- Correlations
Statistical Tests
- One and two-sample t-tests
- One and two-sample binomial tests
- One and two-sample Poisson tests
- Randomization test for two groups
- 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.
- Kruskal-Wallis One-way ANOVA
- Friedman’s Nonparametric ANOVA
- Steel’s Many-one Rank Test
- Cochran’s Q Test
- Cochran-Mantel-Haenszel Test
- Kappa Statistic
- Gamma Statistic
- McNemar’s Test
- Cochran-Armitage Trend Test
- Contingency Tables (Chi-square)
- Goodness of Fit
- MANTEL Test
- W-test for Normality
- Empirical Distribution Tests
- Test for Homogeneity
Distributions
- Fit Distribution
- Probability Plots
- Empirical Tests
- Kernel Density Estimation
- Extremes – Maxima
- Extremes – Observations above Threshold
- Species Abundance Models
Regression Analysis
- Linear Models
- Generalized Linear Models
- Logistic Regression
- Log-linear Models
- Probit Analysis
- Multinomial Regression
- 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
- Parallel Regression
- Lasso Regression
- Response Surface
- Standard Curves
- Nonlinear Models
- Mixed Models – Generalized Linear Mixed Models
- Mixed Models – Hierarchical Generalized Linear Models
- Regression Trees
- Quantile Regression
- Nonlinear Quantile Regression
- Linear Functional Relationship
Design
- Generate a Standard Design
- Generate a Row-Column Design
- Generate a Factorial Design in Blocks
- Generate a Fractional Factorial Design
- Generate a Covariate Design
- Select Design
- Generate Factors in Standard Order
- Randomize Experimental Designs
Analysis of Variance
- One and Two-way
- General Analysis of Variance
- Unbalanced Designs
- Analysis of Variance by ANOVA, Regression or REML
- 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
- Multiple Experiments/Meta Analysis
- Automatic Analysis of Incomplete-Block Design
- Automatic Analysis of Row-Column Design
- Automatic Analysis of Series of Trials
- Generalized Linear Mixed Model
- Hierarchical Generalized Linear Models
Multivariate Analysis
- Principal Components Analysis
- Biplot
- Canonical Variates Analysis
- Discriminant Analysis
- Stepwise Discriminant Analysis
- Principal Coordinates Analysis
- Multidimensional Scaling
- Factor Analysis
- Hierarchical Cluster Analysis
- Non-hierarchical Cluster Analysis
- Procrustes Rotation
- Generalized Procrustes
- Correspondence Analysis
- Multiple Correspondence Analysis
- Canonical Correlations Analysis
- MANOVA
- Canonical Correspondence Analysis
- Redundancy Analysis
- Partial Least Squares
- Multivariate Analysis of Distance
- Regression Trees
- Classification Trees
- Tree Pruning
Six Sigma
- Control Charts for Measurements
- Control Charts for Attributes
- Pareto Chart
- Capability Statistics
- Industrial Designs
Survey Analysis
- Tally Table
- Frequency Tables
- Summary Tables
- Multiple Summary Tables
- Create Survey Weights
- Modify Survey Weights
- Calibration Weighting
- Hot Deck Imputation
- General Survey Analysis
- Single Stage Survey Analysis
- Generalized Linear Models for Survey Data
- Survey Sampling
Time Series
Spatial Statistics
- Contour Plot
- Surface Plot
- Form Variogram
- Model Variogram
- Krige
- Regular Grid (REML)
- Irregular Grid (REML)
- Automatic Analysis of Row-Column Design
- Automatic Analysis of Incomplete-Block Design
- Nearest Neighbour Analysis
- 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
- Profile Plot
- Analysis of Variance
- Antedependence Analysis
- MANOVA
- Correlation Models by REML – Data in Multiple Variates
- Correlation Models by REML – Data in One Variate
- Linear Regression with Correlated Errors
- Standard Curves with Correlated Errors
- Generalized Estimating Equations (GEE)
Meta Analysis
- Finlay & Wilkinson Analysis
- AMMI
- REML for Multiple Experiments
- Meta Analysis for Individual Trials
- Automatic Analysis of Series of Trials
- Multi-treatment Meta Analysis of Summaries
- GGE Biplot
- Stability coefficients
Microarrays
- Design – Generate One Channel
- Design – Generate Two Channel
- Design – Check Two Channel Design
- Open Microarray Data Files
- Calculate – Log-Ratios
- Calculate – Affymetrix Expression Values
- Explore – Histograms
- Explore – Density
- Explore – 2D Plot
- Explore – Spatial Plot
- One channel Quantile Normalization
- Two Channel Microarray data
- Analyse – One Channel ANOVA
- Analyse – One Channel Regression
- Analyse Estimates from Log-Ratios
- Analyse – Empirical Bayes Estimates
- Analyse – False Discovery Rate using Mixture Models
- Analyse – False Discovery Rate using Bonferroni
- Discovery – Q-Q Plot
- Discovery – Volcano Plot
- Cluster – Probes/Genes
- Cluster – Targets/Slides
- Two-way Clustering
Genetic Models
QTLs (Linkage/Association)
- Load Phenotypic data
- Load Genotypic (Marker and Map) data
- Load Genetic Relationship data
- Save Genotypic (Marker and Map) data
- Save Flapjack Project file
Data Manipulation
- Compatibility Check
- Subset Phenotypic and Genotypic data by Genotypes
- Subset Genotypic data by Markers
- Replace Missing Values in Marker Scores
Phenotypic data Exploration
- Summary Statistics Single Environment
- Summary Statistics Multiple Environments
- Summary Statistics Multi-trait
- AMMI
- GGE Biplot
Genotypic data Exploration
Map Construction
Phentotypic Analysis
- Preliminary Single Environment Analysis
- Select Best Variance-Covariance Model for Multiple Environments
Gentotypic Analysis
QTL Analysis
- Single Trait Linkage Analysis (Single Environment)
- Multi-trait Linkage Analysis (Single Environment)
- Single Trait Association Analysis (Single Environment)
- Single Trait Linkage Analysis (Multiple Environments)
- Single Trait Association Analysis (Multiple Environments)
- View QTL data space
Data Mining
- Train Support Vector Machine
- Predict from Support Vector Machine
- Derive Association Rules
- Neural Network
- Discriminant Analysis
- Stepwise Discriminant Analysis
- Hierarchical Cluster Analysis
- Non-hierarchical Cluster Analysis