Scientific Cartography GraphPad Prism 8.0.2.263 Windows x86 x64 Simplified Chinese Wood of Dust

GraphPad Prism It integrates biological statistics, curve fitting and scientific and technological mapping, and its functions are very practical and refined, including some special functions, such as ROC curve analysis, Bland Altman analysis, etc; The curve fitting function is a magic weapon for GraphPad Prism to surpass other statistical software. GraphPad Prism's linear/nonlinear fitting function is extremely convenient to use and operate. It has not only built-in common regression models, but also specially built-in dozens of biostatistics modules, such as Advanced Radioled Bbinding, Bacerial Growth, dose response curve, peak fitting, etc, The drawing function of GraphPad Prism is also very special. There is no need to draw statistical graphs specially. As long as you input data, the graphs will be automatically generated and updated in time as the data changes, which is very convenient and practical.

Among the software that can perform custom equation curve fitting, GraphPad Prism is the most convenient and fast to operate, with convenient parameter setting before fitting, fast fitting speed, and batch fitting support. This is very rare in similar software, so GraphPad Prism is worthy of being an expert in nonlinear fitting.

Prism can be regarded as an alternative software for Sigmaplot in the drawing of scientific charts, but it also includes a simple trial balance, which can directly input the original data, and the software automatically calculates the standard deviation and p value. In addition, it also includes several other numerical analysis capabilities.

Prism 8 Analyze, graph and present your scientific work.

The preferred analysis and graphing solution purpose-built for scientific research. Join the world’s leading scientists and discover how you can use Prism to save time, make more appropriate analysis choices, and elegantly graph and present your scientific research.

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

One-Click Regression Analysis

No other program simplifies curve fitting like Prism. Select an equation and Prism does the rest—fits the curve, displays a table of results and function parameters, draws the curve on the graph, and interpolates unknown values.

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.

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.

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.

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.

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

Find related sheets easily

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.

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

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.
Two-way ANOVA, with repeated measures in one or both factors. Tukey, Newman-Keuls, Dunnett, Bonferroni, Holm-Sidak, or Fisher’s 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).
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.
Compare parameters between data sets.
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.

Linear Regression and Correlation

Calculate slope and intercept with confidence intervals
Force the regression line through a specified point.
Fit to replicate Y values or mean Y.
Test for departure from linearity with a runs test.
Calculate and graph residuals in four different ways (including QQ plot).
Compare slopes and intercepts of two or more regression lines.
Interpolate new points along the standard curve.
Pearson or Spearman (nonparametric) correlation.
Multiple linear regression (including Poisson regression) using the new multiple variables data table.

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.