Min.Version: 2025b (10.25) Updated on: 11/18/2025

Perform binary, multinomial, and ordinal logistic regression.

Min.Version: 2025b (10.25) Updated on: 10/16/2025

Using repeatability and reproducibility analysis to measure the measurement error in measurement systems.

Min.Version: 2025b (10.25) Updated on: 9/17/2025

Perform regression to study the relationship between a response variable and categorical or continuous independent variables.

Min.Version: 2025b (10.25) Updated on: 9/17/2025

Display the correlation coefficient matrix including its P-value in a graph.

Min.Version: 2018 (9.5) Updated on: 6/13/2025

Perform principal component analysis on spectroscopy data.

Min.Version: 2021b (9.85) Updated on: 6/12/2025

Fit the probit analysis procedure.

Min.Version: 2021 (9.8) Updated on: 6/12/2025

Support vector machine for classification.

Min.Version: 2025b (10.25) Updated on: 6/12/2025

Create plots with significant differences for pairwise comparison

Min.Version: 2025b (10.25) Updated on: 6/12/2025

Perform hierarchical cluster analysis along columns and rows, and plot heat map with dendrogram (PRO Only)

Min.Version: 2025b (10.25) Updated on: 6/12/2025

Use a small number of latent variables to explain variability among many observed variables.

Min.Version: 2018b (9.55) Updated on: 6/12/2025

Run redundancy analysis on explanatory data ( x matrix) and response data (y matrix).

Min.Version: 2018 (9.5) Updated on: 6/12/2025

An enhanced version of Principal Component Analysis tool.

Min.Version: 2019b (9.65) Updated on: 11/14/2024

Help to determine the appropriate statistical test/tool/App.

Min.Version: 2022 (9.9) Updated on: 11/6/2024

Perform structural equation modeling optimization.

Min.Version: 2019b (9.65) Updated on: 8/19/2024

Create 3D stacked histograms with distribution curves.

Min.Version: 2017 (9.4) Updated on: 11/20/2023

Create Forest Plot

Min.Version: 2020 (9.7) Updated on: 4/25/2023

Fit Gaussian mixture models and cluster test data.

Min.Version: 2020 (9.7) Updated on: 4/25/2023

Compare parameters across multiple datasets, or compare multiple datasets using a nonlinear model.

Min.Version: 2017 (9.4) Updated on: 2/22/2023

Perform simple time series analysis including autocorrelation, cross correlation, differencing, and single exponential smoothing.

Min.Version: 2017 (9.4) Updated on: 2/3/2023

Compute Allan variance for time series at given tau values.

Min.Version: 2019b (9.65) Updated on: 8/3/2022

Add confidence ellipse to 2D scatter plot

Min.Version: 2016 (9.3) Updated on: 6/15/2022

Calculate Hurst exponent with rescaled range analysis.

Min.Version: 2022b (9.95) Updated on: 1/4/2022

Fit and rank multiple functions to identify best fitting model.

Min.Version: 2019 (9.6) Updated on: 5/31/2019

Plot 3D confidence ellipsoid for 3D scatter data (PRO Only).

Min.Version: 2018b (9.55) Updated on: 4/11/2019

Plot a histogram with logarithmic X scale.

Min.Version: 2018b (9.55) Updated on: 11/27/2018

Perform Cochran's Q test.

Min.Version: 2018 (9.5) Updated on: 1/16/2018

Create 2D means-with-error plot for grouped data.

Min.Version: 2018 (9.5) Updated on: 10/10/2017

Create volcano plot for fold change and p-value data.

Min.Version: 2017 (9.4) Updated on: 5/19/2017

Compare observed and expected frequencies with the Chi-Square test.

Min.Version: 2018 (9.5) Updated on: 5/8/2017

Perform constrained multiple regression and solve constrained linear least-squares problems (PRO Only).

Min.Version: 2018 (9.5) Updated on: 4/26/2017

Test randomness of sequences.

Min.Version: 2017 (9.4) Updated on: 3/2/2017

Calculate ranks of values in a column.

Min.Version: 2017 (9.4) Updated on: 1/20/2017

Perform Weibull fit using rank regression on X

Min.Version: 2017 (9.4) Updated on: 12/9/2016

Generate random/patterned data

Min.Version: 2017 (9.4) Updated on: 10/24/2016

Perform Hotelling's T-squared test to compare multivariate means for two samples or paired samples.

Min.Version: 2016 (9.3) Updated on: 3/4/2016

Simulate your process by supplying a transform equation and distribution parameters for input variables.