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Principal Component Analysis
Calculate and select the principal components that describe the greatest amount of variance in your data. Choose from selection techniques including Parallel Analysis via Monte Carlo simulation, Eigenvalue threshold, Proportion of Variance threshold, and more
Improved grouped graphs
Easily create graphs that show both individual points (scatter) along with bars for mean (or median) and error bars
Analyze categorical variables with text in Multiple Linear and Multiple Logistic Regression
No coding required! Prism will automatically encode categorical variables and perform the analysis. Specify a reference and organize all levels of categorical variables in a model for clear, readable results
Multiple variables data table
Each row represents a different subject and each column is a different variable, allowing you to perform multiple linear regression (including Poisson regression), extract subsets of data into other table types, or select and transform subsets of the data. Prism’s multiple variable tables support text variables and have the ability to define variable types
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