Analyze, Graph and Present your scientific Work
Introducing GraphPad Prism 11, a versatile Statistical Graphing Software used by Scientists, Not Statisticians.
Comprehensive Analysis and Powerful Statistics, Simplified
Organize Your Data Effectively
GraphPad Prism is primarily formatted for the analyses you want to perform, including the study of quantitative and categorical data. This makes it easy to enter data accurately, select acceptable analyses, and create amazing graphs.
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Perform The Right Analysis
Skip the statistical jargon.
GraphPad Prism offers a broad variety of analyses from standard to very specialized: t tests, one-, two- and three-way ANOVA, linear and nonlinear regression, dose-response curves, binary logistic regression, survival analysis, principal component analysis, and many more.
Every study has a checklist to help you understand the necessary statistical assumptions and ensure that you have chosen an acceptable test.
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Simplify the complexity of statistics.
The online help of GraphPad Prism software goes beyond your expectations. Almost any step of the way, you can browse thousands of pages from Prism Guides online.
Browse the Graph Portfolio to learn how to create a wide variety of graph types. Sample data sets help you understand why you should carry certain analyses and how the conclusions can be viewed.
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Work Smarter, Not Harder
GraphPad Prism removes the complexity so you can focus on what matters: your research.
One-Click Regression Analysis
No other software simplifies curve fitting like the way Graphpad Prism 11 does. Just select the equation and Prism does the rest-fits the curve, shows the table of results and function parameters, plots the curve on the graph, and interpolates unknown values.
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Focus on Your Research, Not Your Software
Graphpad Prism 11 does the coding for you. Graphs and results are auto updated in real time. Any modifications in data and analyses-direct data entry, omitting inaccurate data, correcting typos, or modifying analysis methods-are mirrored immediately in graphs, results and layouts.
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Automate Your Work Without Programming
Just one click and automatically apply several pairwise comparisons to the analysis. To configure these lines and asterisks, simply press the Toolbar button again. Make changes to the data or analysis, and the results shown on the graph will be changed automatically.
Start a Free TrialThe Fastest Way to Elegantly Graph and Share Your Work
Countless Ways to Customize Your Graphs
GraphPad Prism is a leader in Scientific Graphing Software. Concentrate on your data story, not configuring your software. GraphPad Prism software makes it simple to build the graphs you like. Choose the graph type, you can literally customize any component on the graph-how the data is structured, the layout of the data points, fonts, colors, labels and more. The possibilities for customization are infinite.
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Explore Data with GraphPad Prism 11
Prism 11 allows you to easily explore large data sets and customize how you view the relationships in your data. You can concentrate your efforts on the most relevant data.
Start a Free TrialExport Publication-Quality Graphs With One Click
Graphpad Prism helps you reduce the time to publish. You can configure your exports (file type, dimensions, resolution, transparency, RGB/CMYK color space) to suit the journal specifications. To save time you can set your defaults.
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Enhance Collaboration
Share more than just the graphs. Graph pad Prism's detailed record of your data makes it possible to have a meaningful cooperation with other scientists. All details of your Prism project (analyses, graphs, raw data, results and layouts) are stored in a single file that you can share with a single click. Now, everyone can conveniently track your work at any stage, increase the clarity of your conclusions and streamline your collective efforts.
Start a Free TrialAccelerate Smarter Data Analysis with GraphPad Prism's Powerful Features
Introducing an even more powerful Prism featuring enhanced data visualization and graph customization, more intuitive navigation, and more sophisticated statistical analyses.
Bubble Plots
Create Bubble Plots directly from raw data, encoding variables for position (X- and Y-coordinates), color, and size
Violin plots
Visualize distributions of large data sets with either extended or truncated violin plots
Estimation Plots
Automatically display your analysis results
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
Frequently Asked Questions
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 total.
Multiple Variable Graphing
- Specify variables defining axis coordinates, color, and size.
- Create Bubble Plots.
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