Principal component analysis and factor analysis software PCA with the most advanced biplot implementation in any commercial statistics package — classical Gabriel and Gower & Hand biplots with interactive reflection, rotation, and scaling. Factor Analysis with 12 rotation methods, Cronbach's alpha, and prediction of new observations.
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Trusted by 75,000 researchers, analysts, and scientists at leading universities, hospitals, and companies worldwide — for over 30 years.
Biplots that make loadings visible
Classical Gabriel biplots and modern Gower & Hand biplots, with interactive reflection, rotation, and scaling. Correlation monoplots for large variable sets. Colour maps on the coefficient matrix reveal which variables load on which components at a glance — not buried in a table of numbers.
12 factor rotation methods
Varimax, Quartimax, Equamax, Oblimin, Promax, and seven more orthogonal and oblique rotations. Factor pattern and structure matrices colour-mapped to reveal factor structure immediately. Maximum likelihood extraction with goodness-of-fit test.
NIST-validated accuracy
All calculations run in Analyse-it's own validated engine — not Excel's built-in functions. Validated against NIST Standard Reference Datasets with IEEE 754 double-precision arithmetic throughout. The same depth as Minitab or JMP, at a fraction of the cost.
Most PCA implementations produce eigenvalues, a scree plot, and a table of component loadings. Analyse-it goes substantially further. Both classical Gabriel biplots (variables as vectors, observations as points) and modern Gower & Hand biplots (both as points), with interactive reflection, rotation, and scaling to find the view that reveals the structure most clearly. Correlation monoplots for when the biplot is too crowded. Colour maps on the coefficient matrix that show the loading pattern at a glance. These are the tools that make PCA results interpretable in practice, and they are rare in commercial statistics software — most packages offer at best a basic scatter of scores.
Factor Analysis complements PCA with 12 orthogonal and oblique rotation methods — from Varimax and Quartimax through to Oblimin, Promax, and Procrustes. Maximum likelihood extraction with a goodness-of-fit test for the number of factors. Factor pattern and structure matrices are colour-mapped so the factor structure is visible immediately, without scanning rows of numbers. Cronbach's alpha for item reliability with deleted-alpha diagnostics, and prediction of new observations from the fitted model.
Analyse-it runs inside Excel with the same task-based workflow used throughout the software. Choose your variables, run the analysis, inspect the biplot, adjust and re-run. Results live in your workbook alongside your data — share the workbook with a colleague and they see everything, whether or not they have Analyse-it installed. No separate application to learn, no proprietary file format, no data import step. The same analytical depth you'd expect from a dedicated statistics package, without the cost of a Minitab or JMP licence or the programming overhead of R.
What's included
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Identify the components that explain your data
Eigenvalues and eigenvectors, coefficient matrix with colour maps, scree plot, and explained variance. Correlation PCA and Covariance PCA. Predict new observations and new variables from the fitted model without manual calculation.
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Interpret results with advanced biplots
Classical Gabriel biplots with variables as vectors and observations as points. Modern Gower & Hand biplots with both as points. Reflect, rotate, and scale interactively to find the most revealing view. Correlation monoplots for large variable sets where the biplot is too crowded.
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Extract latent factors with 12 rotation methods
Maximum likelihood factor extraction. Factor pattern and structure matrices with colour maps. Varimax, Quartimax, Equamax, Parsimax, Oblimin, Quartimin, Promax, Procrustes, and more. Goodness-of-fit test for the number of factors.
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Measure correlation across your full variable set
Pearson, Spearman, and Kendall correlation coefficients with confidence intervals and significance tests. Correlation and covariance matrices with colour maps. Scatter plot matrices with optional factor colouring to reveal group structure.
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Assess scale reliability with Cronbach's alpha
Unstandardized and standardized Cronbach's alpha for internal consistency. Deleted-alpha for each item identifies which items weaken or strengthen the scale — essential when developing or evaluating a measurement instrument.
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Part of the Standard edition
PCA and Factor Analysis are part of the Standard edition, which also covers ANOVA and ANCOVA, simple and multiple regression, logistic regression, descriptive analysis, hypothesis testing, and categorical data analysis. All the professional statistics you'd expect from Minitab or SPSS — at a fraction of the cost, without leaving Excel.
Trusted by 75,000 researchers, analysts, and scientists at leading universities, hospitals, and companies worldwide — for over 30 years.
Try free for 15 days — no credit card required
