Regression analysis software with full diagnostics Simple, multiple, polynomial, and logistic regression — with parameter estimates, confidence intervals, VIF, leverage plots, residual diagnostics, outlier and influence analysis, and prediction. Build the model, examine it, refine it, and predict from it in one workflow.
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.
The complete model-building workflow
Parameter estimates with confidence intervals and VIF. Standardized betas. Type I and Type III tests for every term. R-squared, adjusted R-squared, AIC, BIC. The model equation for documentation and prediction. Not just coefficients — everything you need to understand and defend the model.
Diagnostics that reveal problems
Leverage plots to see each predictor's contribution after accounting for all others. Residual plots, sequence plots, and distribution plots. Outlier and Influence plot using Cook's D and Studentised Residuals. Know whether your model is trustworthy before you act on it.
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.
Excel's built-in regression produces a static output table with coefficients and an R-squared. No diagnostics, no way to check whether the model assumptions hold, no way to identify influential observations that might be driving the result, and no way to iterate. LINEST gives numbers but no understanding. For anything beyond simple linear regression — polynomial terms, categorical factors, interactions, logistic regression — there is no built-in tool at all.
Analyse-it treats regression as a process of building, examining, and refining a model. Start with your data, choose the model structure — simple linear, polynomial up to 6th order, logarithmic, exponential, power, probit, or multiple regression with any combination of continuous and categorical predictors, crossed terms, and interactions. Get the complete output: parameter estimates with confidence intervals, VIF for multicollinearity, standardized betas, Type I and Type III hypothesis tests for each term, R-squared, adjusted R-squared, AIC, BIC, and the model equation. Then examine the diagnostics — leverage plots, residual plots, outlier and influence analysis — and refine. Add or remove terms, transform variables, re-run. The results update immediately in the same workbook.
For models with categorical predictors, Analyse-it codes dummy variables automatically and provides effect means with confidence intervals, main effect and interaction plots, and the same nine multiple comparison procedures available in ANOVA — Tukey-Kramer, Dunnett, Hsu, Scheffe, and more. For binary outcomes, logistic regression is included with odds ratios, model fit statistics, and influence diagnostics. Save fitted values, residuals, leverage, and Cook's D back to the dataset, or predict new observations directly from the fitted model.
75,000 researchers, analysts, and scientists at leading universities, hospitals, and companies worldwide have relied on Analyse-it for over 30 years.
What's included
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Fit simple and curve regression models
Linear, polynomial (2nd to 6th order), logarithmic, exponential, power, and probit regression. Transform X and Y variables. F-test for lack of fit. Scatter plot with fit line and confidence bands.
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Build complex models with multiple predictors
Any combination of continuous and categorical predictors. Simple, crossed, polynomial, and factorial terms. Categorical variables coded automatically as dummy variables. Full factorial and custom model structures. ANOVA and ANCOVA models with adjusted effect means.
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Model binary outcomes with logistic regression
Binary logistic regression with parameter estimates, odds ratios, confidence intervals, AIC/BIC, likelihood-ratio and Wald tests, leverage plots, and influence diagnostics. See logistic regression details.
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Assess each predictor's contribution independently
Sequential (Type I) and partial (Type III) hypothesis tests for every term. Leverage plots to visualise the effect of each predictor after accounting for all others. VIF for multicollinearity. Standardized betas for comparing predictor importance.
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Identify problems before they undermine your conclusions
Raw and standardised residual plots, sequence and lag plots, residual distribution. Outlier and Influence plot using Cook's D and Studentised Residuals. Know whether individual observations are driving the model before you report the results.
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Save model variables and predict new observations
Save fitted values, residuals, standardised residuals, studentised residuals, leverage, and Cook's D back to the dataset. Predict new observations directly from the fitted model without manual calculation.
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Part of the Standard edition
Regression is part of the Standard edition, which also covers ANOVA and ANCOVA, PCA and factor analysis, logistic regression, descriptive analysis, hypothesis testing, and categorical data analysis. All the professional statistics you need — at a fraction of the cost of dedicated packages.
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
