statistiXL is a powerful data analysis package that runs as an add-in to Windows versions of Microsoft Excel. statistiXL has been entirely designed and written by scientists in order to meet the demanding needs of anyone requiring a robust, versatile statistical analysis package that is quick to learn and easy to use. With its wealth of features, Excel provides an ideal environment for data input, manipulation and calculation and by leveraging this familiar environment, statistiXL greatly extends this feature set to encompass high powered statistical analysis without the need to learn how to use an entirely new application. Data stored in existing spreadsheets can instantly be subjected to a wide range of statistical tests (many frequently not seen in other analysis packages). Tests provided by statistiXL include (but are not limited to), Analysis of Variance, Cluster Analysis, Contingency Tables, Correlation (Simple, Partial, Multiple and Canonical), Linear and Circular Descriptive Statistics, Classification and Grouping Discriminant Analysis, Factor Analysis, Goodness of Fit Tests such as Binomial, Circular, Normal and Poisson, Simple and Multiple Linear Regression, Regression Comparison, Nonparametric Tests such as Friedman, Kruskal-Wallis and Mann-Whitney, Principal Component Analysis, Univariate and Multivariate t-Tests. statistiXL also produces a wide range of plots including Box and Whisker Plots, Scatter Plots, Clustering Dendrograms, Normal Probability Plots and many others. Numerous options exist for formatting the standard results that are outputted by statistiXL and because these results are placed into Excel spreadsheets, you can use the tools that you are already familiar with to arrange and format textual and graphical output even further, changing fonts, rearranging cells, altering the scale on the axis of a graph etc etc. You can even subject the results to further analysis using either statistiXL or any of Excels numerous built in functions.
Microsoft Excel 97, 2000, XP, 2003, 2007, 2010, 2013, 2016 or newer
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