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Introduzione in Italiano

InStat
È un semplice pacchetto di statistica che permette di utilizzare procedure statistiche con semplicità e velocità. A differenza di software molto più potenti (e costosi) InStat è lo strumento ideale per coloro che, non specializzati nella statistica, devono analizzare piccoli set di dati.

InStat is available for both Windows and Mac!

InStat helps scientists and students conquer routine statistical procedures with speed and ease. Unlike larger (and much more expensive) packages, InStat is designed for scientists and students analyzing small amounts of data. InStat takes just minutes to master, and can be a perfect companion to complex programs. Here is what makes InStat stand out from other statistics programs:

InStat guides you step by step

InStat conquers the learning curve by escorting you through statistical analyses one step at a time. You’ll master the program in minutes – really.

Clear choices with explanations

Don’t know the name of the test you need? InStat helps you choose a test by asking you questions about your data. If you are unsure, consult the extensive help screens, which explain the statistical reasoning in plain language.

Easy to understand results

InStat doesn’t assume that you are a statistics whiz. It presents results in simple paragraphs, with a minimum of statistical jargon. InStat’s help screens review the use of each test and explain every portion of the results.

Unique analysis checklists

With other statistics software, it is too easy to get the right answer to the wrong question. That is why InStat provides unique analysis checklists to assure that your data have not violated any assumptions of the test, and that you have chosen a test that matches your experimental design – and really answers the question you had in mind.

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Features

Most statistics programs are designed by statisticians, for statisticians. These programs are feature-packed and powerful, but can overwhelm scientists with thick manuals, obscure statistical jargon and high prices. GraphPad InStatS®S is different. Designed by a scientist for scientists.

Group comparisons
Unpaired t test or the nonparametric Mann-Whitney test.

Welch's unpaired t test (does not assume equal standard deviations)

Paired t test or the nonparametric Wilcoxon matched pairs test.

Ordinary one-way ANOVA or the nonparametric Kruskal-Wallis test.

Repeated measures one-way ANOVA (identical to two-way ANOVA without replication) or the nonparametric Friedman test.

Follow ANOVA with the Bonferroni, Tukey, Student-Newman-Keuls or Dunnett multiple comparison post test, or with the post test for linear trend.

Follow nonparametric ANOVA with Dunn's post test.

One sample t test or the nonparametric Wilcoxon rank sum test.

F test or Bartlett's test to test for equality of standard deviations.

Perform unpaired t tests and ordinary ANOVA from either raw data or mean, N and SD (or SEM).

Allows missing values in ordinary ANOVA and unpaired t tests.

Calculate mean, SD, SEM, minimum, Maximum and median of each group, and the 95% confidence interval of the group mean.

Kolmogorov-Smirnov normality test.

View bar graph of group means and SD or SEM.

 

Contingency tables
Chi-square test with or without Yates' continuity correction.

Chi-square test for linear trend.

Fisher's exact test.

Calculate 95% confidence intervals for the relative risk, odds ratio or difference between two proportions.

Calculate the sensitivity, specificity,positive predictive value, negative predictive value and likelihood ratio of a diagnostic test, with 95% confidence intervals.

 

Linear regression and correlation

Calculate slope and intercept with 95% confidence intervals.

Force the regression line through a specified point.

Determine new points along the standard curve.

Calculate correlation coefficient (Spearman or Pearson) and its confidence interval.

Test for departure from linearity with a runs test or the F test for linearity.

View scatter plot with regression line and its 95% confidence interval.

 

Multiple regression and correlation
Calculate a correlation matrix.

Multiple regression using selected X variables.

For each X variable, compute its best-fit coefficient with standard error and 95% confidence interval, and a P value testing whether the variable contributes significantly to the model.

Compute the Variable Inflation Factor (VIF) to test for multicollinearity (whether the variable is redundant).

 

Program features

Enter up to 1000 (Windows) rows and 26 columns of data.

Mathematically transform selected data (i.e., logarithm, reciprocal, logit, etc.).

Transpose Paste. Transpose rows and columns.

Copy results or data to the Macintosh or Windows clipboard, or export as a text file.

Print graphs on any printer or export as Windows Metafile (.WMF) or PICT (Mac) files.

Annotate your data and analyses using a built-in notes editor. Notes are included in the data files.

InStat files contain analysis choices as well as data so you can quickly rerun the same test with multiple sets of data.

Combine two columns (add, subtract, multiply, divide) to create a new column.

Import data from comma or tab delimited test files.

Import indexed (stacked) data, entire tables or selected rows and columns, filter selected data.

Export the data table as a text table, or as indexed (stacked) file.

Exclude selected values. They appear on the data table, but are treated as missing values by the analyses.

 

What InStat does not do
InStat is not for everyone. It performs basic tests easily, but does not handle advanced statistical tests. For example, InStat does not perform two-way (or higher) ANOVA, logistic regression, the Mantel-Haenszel test (to analyze a stack of contingency tables), stepwise multiple regression, analyses of survival curves, analysis of covariance, factor or cluster analysis, polynomial regression or nonlinear regression. InStat is an ideal tool for analyzing experimental data and data from small clinical studies, but is not designed to analyze large clinical studies. InStat has limited ability to select a subset of cases from a large file and cannot cross-tabulate data to form a contingency table.

System requirements