PCA Software for Microsoft Excel
Principal Component Analysis and Factor Analysis in Excel — with the most advanced biplot implementation available in any commercial statistics package. Understand what’s driving your data without leaving your spreadsheet.
Try free for 15 days — no credit card required
Trusted by 75,000 researchers, analysts, and scientists at leading universities, hospitals, and companies worldwide — for over 30 years.
See what’s actually driving your data
When you have many variables and can’t see the structure beneath them, PCA reveals it. Analyse-it’s PCA finds the underlying components, shows you how variables relate to each other, and identifies distinct groupings of observations — all presented in visualizations that make the patterns immediately visible.
The most advanced biplots in any commercial package
Biplots are where PCA becomes interpretable. Analyse-it implements both classical Gabriel biplots and modern Gower & Hand biplots, with the ability to reflect, rotate, and scale them interactively. It’s likely the most complete biplot implementation available in any commercial statistics software.
PCA without leaving Excel
Your data is in Excel. The analysis runs in Excel. The biplots, scree plots, color maps, and factor loadings all appear in your workbook, ready to share, annotate, or use in a report. No export, no separate application, no format conversion.
Complex datasets have a common problem: the important structure is buried. You have many variables, many observations, and no clear way to see which variables are related, which observations cluster together, or what underlying factors are driving the patterns you care about.
PCA solves this by finding the dimensions along which your data actually varies. But a good PCA implementation is more than eigenvalues and a scree plot. The value is in the visualization: biplots that show how variables and observations relate in the same space, color maps that reveal correlation structure in large matrices, and mono-plots that make the relationships between variables clear.
Analyse-it implements PCA at the depth of a professional statistical package — including Factor Analysis with 12 rotation methods, prediction of new observations, and Cronbach’s alpha for item reliability — all within Excel, with the same task-based workflow used throughout the software.
What's included
- Principal Component Analysis (PCA) Eigenvalues and eigenvectors, coefficient matrix, scree plot, and explained variance. Correlation and Covariance PCA. Color maps for the coefficient matrix to reveal which variables load on which components. Predict new observations and new variables from the model.
- Advanced biplots Classical Gabriel biplots with variables as vectors and observations as points. Modern Gower & Hand biplots with both variables and observations as points. Reflect, rotate, and scale biplots interactively. Correlation monoplots to show relationships between variables clearly.
- Common Factor Analysis Maximum likelihood factor extraction. Factor pattern and structure matrices with color maps to reveal factor structure. 12 orthogonal and oblique rotation methods including Varimax, Quartimax, Oblimin, Promax, and more.
- Correlation and association Pearson, Spearman, and Kendall correlation coefficients with confidence intervals. Correlation and covariance matrices. Scatter plots and scatter plot matrices with optional factor coloring.
- Item reliability (Cronbach’s alpha) Unstandardized and standardized Cronbach’s alpha. Deleted alpha for each item to identify which items weaken or strengthen the scale.
- More than just PCA PCA and Factor Analysis are part of the Standard edition, which also covers descriptive analysis, hypothesis testing, ANOVA, regression, ANCOVA, and categorical data analysis — all in the same Excel workflow.
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Try free for 15 days — no credit card required
