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Comprehensive Analysis and Powerful Statistics, Simplified

Organize Your Data Effectively

Unlike spreadsheets or other scientific graphing programs, Prism has eight different types of data tables specifically formatted for the analyses you want to run. This makes it easier to enter data correctly, choose suitable analyses, and create stunning graphs.

Perform The Right Analysis

Avoid statistical jargon. In clear language, Prism presents an extensive library of analyses from common to highly specific—nonlinear regression, t tests, nonparametric comparisons, one-, two- and three-way ANOVA, analysis of contingency tables, survival analysis, and much more. Each analysis has a checklist to help you understand the required statistical assumptions and confirm you have selected an appropriate test.

Get Actionable Help As You Go

Reduce the complexity of statistics. Prism’s online help goes beyond your expectations. At almost every step, access thousands of pages from the online Prism Guides. Browse the Graph Portfolio and learn how to make a wide range of graph types. Tutorial data sets also help you understand why you should perform certain analyses and how to interpret your results.

Work Smarter, Not Harder

Focus on Your Research, Not Your Software
No coding required. Graphs and results are automatically updated in real time. Any changes to the data and analyses—adding missed data, omitting erroneous data, correcting typos, or changing analysis choices—are reflected in results, graphs, and layouts instantaneously.
One-Click Regression Analysis
Reduce the complexity of statistics. Prism’s online help goes beyond your expectations. At almost every step, access thousands of pages from the online Prism Guides. Browse the Graph Portfolio and learn how to make a wide range of graph types. Tutorial data sets also help you understand why you should perform certain analyses and how to interpret your results.
Automate Your Work Without Programming
Reduce tedious steps to analyze and graph a set of experiments. It is easy to replicate your work by creating a template, duplicating a family, or cloning a graph—saving you hours of set up time. Apply a consistent look to a set of graphs with one click using Prism Magic.

The Fastest Way to Elegantly Graph and Share Your Work

Countless Ways to Customize Your Graphs

Focus on the story in your data, not manipulating your software. Prism makes it easy to create the graphs you want. Choose the type of graph, and customize any part—how the data is arranged, the style of your data points, labels, fonts, colors, and much more. The customization options are endless.

Enhance Collaboration

Share more than your graphs. Prism’s comprehensive record of your data enables effective collaboration with other scientists. All parts of your Prism 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.

Export Publication-Quality Graphs With One Click

Reduce time to publish. Prism allows you to customize your exports (file type, resolution, transparency, dimensions, color space RGB/CMYK) to meet the requirements of journals. Set your defaults to save time.

Discover What’s New in Prism 8!

Introducing an even more powerful Prism featuring enhanced data visualization and graph customization, more intuitive navigation, and more sophisticated statistical analyses.

Enhanced Data Visualization

Violin plots
Visualize distributions of large data sets more clearly than with box-whisker or simple bar graphs
Subcolumn graphs
Organize related subsets of nested data in a single graph
Smoothing spline
Major improvements in showing general data trends through Akima splines and smoothing
splines with improved control over the number of knots, or inflection points
No more smiles
More intelligent adjustments of data point positions in scatter plots for better looking graphs

Improved Graphing and Customization Options

Draw lines and brackets with centered text
Easily annotate your data with asterisks or custom labels
Automatically label bar graphs
Annotate your bar graphs with values for the means, medians, or sample sizes to emphasize what’s important in your work
Improved grouped graphs
Easily create graphs that show both individual points (scatter) along with bars for mean (or median) and error bars

More Intuitive Navigation

Improved grouped graphs
New family panel shows the family of sheets related to the current sheet, and chains
of analyses are automatically indented
Easily navigate between multiple results tables
Analyses with multiple results tables now grouped into a single sheet with tabs for
each result table; choose which tabs to show or hide
Improved Search
Search by sheets with highlights or notes of specified color

Now Featuring Eight Kinds of Data Tables

New: Multiple variables data table
Each row represents a different subject and each column is a different variable,
allowing you to perform Multiple linear regression (including Poisson regression),
extract subsets of data into other table types, or select and transform subsets of the data
New: Nested data table
Analyze and visualize data that contains subsets within related groups; Perform
nested t tests and nested one-way ANOVA using data within these tables

More Sophisticated Statistical Analyses

Perform repeated measures ANOVA – even with missing data
Now Prism will automatically fit a mixed effects model to complete this analysis
Powerful Improvements in regular ANOVA
View cell, row, column, and grand means (or least square means when data is
missing); test for homogeneity of variance. For one-way ANOVA, choose a test
that does not assume homogeneous variances.
Perform simple and multiple logistic regression
Fit a model to a binary outcome (yes/no, win/lose, pass/fail) based on one predictor
variable (simple logistic regression) or many predictor variables (multiple logistic regression).
Nested t test and nested one-way ANOVA
Utilize new types of data tables to perform nested t-tests and nested ANOVA as well
as multiple linear regression (including Poisson regression)
Graph residuals from multiple types of analyses
Test residuals for normality in four different ways, and choose from four different ways to display these residuals
Wave Wave

Discover the Breadth of Statistical Features Available in Prism 8

Statistical Comparisons

  • Paired or unpaired t tests. Reports P values and confidence intervals.
  • Automatically generate volcano plot (difference vs. P value) from multiple t test analysis.
  • Nonparametric Mann-Whitney test, including confidence interval of difference of medians.
  • Kolmogorov-Smirnov test to compare two groups.
  • Wilcoxon test with confidence interval of 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 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.
  • One-way ANOVA without assuming populations with equal standard deviations using Brown-Forsythe and Welch ANOVA, followed by appropriate comparisons tests (Games-Howell, Tamhane T2, Dunnett T3)
  • Many multiple comparisons test are accompanied by confidence intervals and multiplicity adjusted P values.
  • Greenhouse-Geisser correction so repeated measures one-, two-, and three-way ANOVA do 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. Calculate the relative risk and odds ratio with confidence intervals.
  • Two-way ANOVA, even with missing values with some post tests.
  • Three-way ANOVA (limited to two levels in two of the factors, and any number of levels in the third).
  • Analysis of repeated measures data (one-, two-, and three-way) using a mixed effects model (similar to repeated measures ANOVA, but capable of handling missing data).
  • Kaplan-Meier survival analysis. Compare curves with the log-rank test (including test for trend)
  • Comparison of data from nested data tables using nested t test or nested one-way ANOVA (using mixed effects model).

Nonlinear Regression

  • Fit one of our 105 built-in equations, or enter your own. Now including family of growth equations: exponential growth, exponential plateau, Gompertz, logistic, and beta (growth and then decay).
  • Enter differential or implicit equations.
  • Enter different equations for different data sets.
  • Global nonlinear regression – share parameters between data sets.
  • Robust nonlinear regression.
  • Automatic outlier identification or elimination.
  • Compare models using extra sum-of-squares F test or AICc.
  • Apply constraints.
  • Differentially weight points by several methods and assess how well your weighting method worked.
  • Accept automatic initial estimated values or enter your own.
  • Automatically graph curve over specified range of X values.
  • Quantify precision of fits with SE or CI of parameters. Confidence intervals can be symmetrical (as is traditional) or asymmetrical (which is more accurate).
  • Quantify symmetry of imprecision with Hougaard’s skewness.
  • Plot confidence or prediction bands.
  • Test normality of residuals.
  • Runs or replicates test of adequacy of model.
  • Report the covariance matrix or set of dependencies.
  • Easily interpolate points from the best fit curve.
  • Fit straight lines to two data sets and determine the intersection point and both slopes.

Column Statistics

  • Calculate descriptive statistics: min, max, quartiles, mean, SD, SEM, CI, CV, skewness, kurtosis.
  • Mean or geometric mean with confidence intervals.
  • Frequency distributions (bin to histogram), including cumulative histograms.
  • Normality testing by four methods (new: Anderson-Darling).
  • Lognormality test and likelihood of sampling from normal (Gaussian) vs. lognormal distribution.
  • Create QQ Plot as part of normality testing.
  • One sample t test or Wilcoxon test to compare the column mean (or median) with a theoretical value.
  • Identify outliers using Grubbs or ROUT method.
  • Analyze a stack of P values, using Bonferroni multiple comparisons or the FDR approach to identify “significant” findings or discoveries.

Generalized Linear Models (GLMs)

  • Generate models relating multiple independent variables to a single dependent variable using the new multiple variables data table.
  • Multiple linear regression (when Y is continuous).
  • Poisson regression (when Y is counts; 0, 1, 2, …).
  • Logistic regression (when Y is binary; yes/no, pass/fail, etc.).

Clinical (Diagnostic) Lab Statistics

  • Bland-Altman plots.
  • Receiver operator characteristic (ROC) curves.
  • Deming regression (type ll linear regression).

Simulations

  • Simulate XY, Column or Contingency tables.
  • Repeat analyses of simulated data as a Monte-Carlo analysis.
  • Plot functions from equations you select or enter and parameter values you choose.

Other Calculations

  • Area under the curve, with confidence interval.
  • Transform data.
  • Normalize.
  • Identify outliers.
  • Normality tests.
  • Transpose tables.
  • Subtract baseline (and combine columns).
  • Compute each value as a fraction of its row, column or grand to
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