Analyse-it for Microsoft Excel for Windows

Name: Analyse-it for Microsoft Excel
Rating: 5 (1 reviews)
Author: Analyse-it Software

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Developer’s Description

By Analyse-it Software

Statistical analysis add-in software for Microsoft Excel.

Analyse-it integrates into Microsoft Excel to provide in-depth powerful statistical analysis and data visualization. It runs entirely in Microsoft Excel. No data transfer to another application, leaving your data locked in a separate application. And no learning curve because you never leave the familiar Excel environment. Describe.Get concise numerical insight into your data. All the standard statistics are included for central location, dispersion, distribution shape, and association so you can describe data.Infer.Estimate and test hypotheses about location, dispersion, association, differences in means and proportions, homogeneity of variances, and more.Hypotheses and the conclusion of tests test are stated in clear simple language. And p-values are automatically calculated, using exact distributions for small-sample sizes where possible, so you won't need to dust-off your old reference books. What's more, every estimate includes a confidence intervals computed using the latest methods (not found in most packages), to express the uncertainty in the estimate.Fit.Uncover simple and complex relationships between variables with model fitting and regression. Fit linear regression, polynomial regression, logarithmic, exponential, power and binary logistic regression models quickly. Or build your own complex multiple regression models from simple, crossed, factorial and polynomial terms.All backed up with plots and tests that let you verify model assumptions and check the model fit. What's more you can use your newly found knowledge to make future predictions.Visualize.Visualization is essential in any analysis. But the basic charts provided in Microsoft Excel and other add-ins just don't cut it.Analyse-it changes that. Visualize the distribution, see patterns, and spot outliers in your data with univariate statistical plots including box-whisker plots, dot plots, mean plots and histograms. See changes with difference plots. And scatter plots and matrices are included so you can identify bivariate relationships.