The spreadsheet is a valuable tool for data scientist. This is what the annual KDnuggets polls reveal during these last years where Excel spreadsheet is always well placed. In France, this popularity is largely confirmed by its almost systematic presence in job postings related to the data processing (statistics, data mining, data science, big data/data analytics, etc.). Excel is specifically referred, but this success must be viewed as an acknowledgment of the skills and capabilities of the spreadsheet tools.

This tutorial is devoted to the

Gnumeric Spreadsheet 1.12.12. It has interesting features: Setup and installation programs are small because it is not part of an office suite; It is fast and lightweight; It is dedicated to numerical computation and natively incorporates a "statistics" menu with the common statistical procedures (parametric tests, non-parametric tests, regression, principal component analysis, etc.); and, it seems more accurate than some popular spreadsheets programs. These last two points have caught my attention and have convinced me to study it in more detail. In the following, we make a quick overview of Gnumeric's statistical procedures. If it is possible, we compare the results with those of

**Tanagra 1.4.50**.

**Keywords**: gnumeric, spreadsheet, descriptive statistics, principal component analysis, pca, multiple linear regression, wilcoxon signed rank test, welch test unequal variance, mann and whitney, analysis of variance, anova

**Tanagra components**: MORE UNIVARIATE CONT STAT, PRINCIPAL COMPONENT ANALYSIS, MULTIPLE LINEAR REGRESSION, WILCOXON SIGNED RANKS TEST, T-TEST UNEQUAL VARIANCE, MANN-WHITNEY COMPARISON, ONE-WAY ANOVA

**Tutorial**:

en_Tanagra_Gnumeric.pdf
**Dataset **:

credit_approval.zip
**References **:

Gnumeric, "

The Gnumeric Manual, version 1.12".