Products

Banche Popolari Unite Analyzes Credit Risk Using MATLAB

"The numerical computation and visualization capabilities of MATLAB are incredible! We can implement up to 100,000 simulations to hundreds of thousands of positions and relative aggregations quickly." - Roberto Modafferi, Banche Popolari Unite

Toyota Racing Development Makes Faster and More Efficient Engineering Decisions with MATLAB

"We get more data than we can possibly sift through. MATLAB is our workhouse for viewing, sharing, and processing that data." - Skip Essma, Toyota Racing Development

Statistics Toolbox

Perform statistical modeling and analysis

Statistics Toolbox provides algorithms and tools for organizing, analyzing, and modeling data. You can use regression or classification for predictive modeling, generate random numbers for Monte Carlo simulations, use statistical plots for exploratory data analysis, and perform hypothesis tests.

For analyzing multidimensional data, Statistics Toolbox includes algorithms that let you identify key variables that impact your model with sequential feature selection, transform your data with principal component analysis, apply regularization and shrinkage, or use partial least squares regression.

Statistics Toolbox includes specialized data types for organizing and accessing heterogeneous data. Dataset arrays store numeric data, text, and metadata in a single data container. Built-in methods enable you to merge datasets using a common key (join), calculate summary statistics on grouped data, and convert between tall and wide data representations. Categorical arrays provide a memory-efficient data container for storing information drawn from a finite, discrete set of categories.

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