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Prism’s comprehensive record of your data enables effective collaboration with other scientists. All parts of your project (raw data, analyses, results, graphs, and layouts) are contained in a single file that you can share with one click. Now others can easily follow your work at every step, enhancing the clarity of your findings and streamlining your collaborative efforts. Reports P values and confidence intervals. Nonparametric Mann-Whitney test, including a confidence interval of difference of medians.

Kolmogorov-Smirnov test to compare two groups.

Wilcoxon test with a confidence interval of the median.

Perform many t-tests at once, using False Discovery Rate (or Bonferroni multiple comparisons) to choose which comparisons are discoveries to study further.

Ordinary or repeated measures one-way ANOVA followed by the Tukey, Newman-Keuls, Dunnett, Bonferroni or Holm-Sidak multiple comparison tests, the post-test for trend, or Fisher’s Least Significant tests.

Many multiple comparisons tests are accompanied by confidence intervals and multiplicity adjusted P values.

Greenhouse-Geisser correction so repeated measures one-way ANOVA does not have to assume sphericity.

When this is chosen, multiple comparison tests also do not assume sphericity.

Kruskal-Wallis or Friedman nonparametric one-way ANOVA with Dunn's post-test.

Fisher's exact test or the chi-square test.

Two-way ANOVA, even with missing values with some post-tests.Ĭalculate the relative risk and odds ratio with confidence intervals.

Two-way ANOVA, with repeated measures in one or both factors.

Tukey, Newman-Keuls, Dunnett, Bonferron, Holm-Sidak, or Fishers LSD multiple comparisons testing main and simple effects.

Three-way ANOVA (limited to two levels in two of the factors, and any number of levels in the third).

Calculate min, max, quartiles, mean, SD, SEM, CI, CV.Ĭompare curves with the log-rank test (including a test for trend).Mean or geometric means with confidence intervals.Frequency distributions (bin to histogram), including cumulative histograms.One sample t-test or Wilcoxon test to compare the column mean (or median) with a theoretical value.Deming regression (type ll linear regression).Receiver operator characteristic (ROC) curves.Analyze a stack of P values, using Bonferroni multiple comparisons or the FDR approach to identify "significant" findings or discoveries.Pearson or Spearman (nonparametric) correlation.Interpolate new points along the standard curve.Compare slopes and intercepts of two or more regression lines.Test for departure from linearity with a runs test.Force the regression line through a specified point.Calculate slope and intercept with confidence intervals.Identify outliers using Grubbs or ROUT method.