StatFi

Empower Microsoft Excel with accurate statistics
and powerful data analysis

    Unleash the full power of precise statistical analysis in Microsoft Excel. Perform complex data analysis in the familiar environment. No need to learn the new tricks with StatFi!
    Bare Microsoft Excel is of very limited use for performing complex statistical analysis. Unless your analysis setup as basic as simple summaries or simple tests, and unless the precision requirements are rough, using Excel to perform the analytical tasks is a bad idea. The lack of repeatability and reproducibility of results makes Excel less than a perfect tool for statistical data analysis.
    Why? Because Microsoft Excel is, in the essence, not a statistics package. The free Analysis ToolPak add-in supplied with Microsoft Excel is of very limited capability, and is no easier to use than the full-scale dedicated statistical and analytical packages.
    Heavy-duty stand-alone statistical packages are widely available on the market. But are you prepared to learn the new workflow? Switching applications means learning how to use the new tool, possibly spending hours to learn about the features you might never need. Considering the cost of most stand-alone analytical packages, they are ruled out of the equation by many users.

    Fortunately, your choice is not limited to either Excel or industrial software. StatFi expands the statistical and analytical abilities of Microsoft Excel, adding precise calculations and reproducible results with ISO-compliant implementation of the main routines. StatFi enables you to perform analytical and statistical calculations such as normality tests, Pagurova Criterion, correlation coefficients, ANOVA and GLM ANOVA, regression analysis, parametric and non-parametric analysis. The routines such as contingency tables analysis, rank correlations, Probit and Latin squares, Kruskal-Wallis ANOVA and Cochran Q test are also supported.

More information

Statistical features:

• basic statistics:
  • determining descriptive statistics
  • normality tests
  • T-Test/Pagurova Criterion/G-Criterion
  • Fisher F-test
  • correlation coefficients (Pearson, Fechner) and covariation
  • cross-tabulation
  • frequency tables analysis
• ANOVA (MANOVA, GLM ANOVA, Latin squares analysis)
• nonparametric statistics:
  • 2x2 Tables Analysis (Chi-square, Yates Chi-square, Exact Fisher Test, etc.)
  • rank correlations (Kendall Tau, Spearman R, Gamma, etc.)
  • comparing independent samples (Mann-Whitney U Test, Kolmogorov-Smirnov test, Wald-Wolfowitz Runs Test, Rosenbaum Criterion;Kruskal-Wallis ANOVA, median test)
  • comparing dependent samples (Wilcoxon Matched Pairs Test, Sign Test, Friedman ANOVA, Kendall's Coeff. of Concordance)
  • Cochran Q Test
• regression analysis:
  • multivariate linear regression
  • logistic regression
  • stepwise regression
  • polynomial regression
  • Cox proportional-hazards regression
• time series analysis
• survival analysis
  • Cox regression
  • probit-analysis (LD50, LD50 SE, cumulation coefficient, LD100 calculation)