GraphPad Prism 10.3.1.509 Full Version | DownloadPirate

By | September 21, 2024

Details of GraphPad Prism 10.3.1.509:

GraphPad-Prism-Free-full-DownloadDraphPad Prism Full Version is recommended graphing and analysis tool designed specifically for scientific investigations. Discover how to use Prism to expedite your research, make better analysis decisions, and present your findings in an elegant manner by joining the top scientists in the world.

Benefits of GraphPad Prism 10.3.1.509:

  • Organize Your Data Effectively:

DraphPad Prism Latest Version is formatted especially for the types of analyses you wish to perform, such as categorical and quantitative data analysis. This facilitates accurate data entry, the selection of pertinent analyses, and the creation of eye-catching graphs.

  • Sample Size and Power Analysis:

DraphPad Prism Full Download start your experiments as efficiently as possible by precisely estimating the sample size required for the effect you anticipate, or look into the smallest effect you can find with a small sample size. Simplify your research procedure, protect priceless resources, and increase the validity of your conclusions.

  • Perform the Right Analysis:

Steer clear of statistical jargon. Prism provides a vast library of analyses, ranging from widely used to highly specialized, in an easy-to-understand manner. These analyses include survival analysis, principal component analysis, binary logistic regression, one-, two-, and three-way ANOVA, t tests, linear and nonlinear regression dose-response curves, and much more. Every analysis comes with a checklist to help you make sure you’ve chosen the right test and comprehend the necessary statistical assumptions.

  • Get Actionable Help as You Go:

Cut down on the statistical intricacy. DraphPad Prism web assistance surpasses your anticipations. Access thousands of pages from the Prism User Guides at nearly every turn. With Prism Academy, you can access instructional videos, manuals, and other resources. Learn how to create a variety of graph types by looking through the Graph Portfolio. Tutorial data sets also assist you in comprehending the rationale behind specific analyses and the interpretation of your findings.
One-Click Regression Analysis:

Prism is the only program that makes curve fitting so much easier. Once you choose an equation, Prism takes care of the rest, fitting the curve, displaying the function parameters and results in a table, graphing the curve, and interpolating unknown values.

  • Focus on Your Research, Not Your Software:

You can leave the coding to Prism. Real-time automatic updates are made to the graphs and results. Results, graphs, and layouts instantly update in response to any modifications made to the data and analyses, including direct data entry, the removal of incorrect data, typo corrections, and altered analysis selections.

  • Automate Your Work Without Programming:

A single click, automatically add numerous pairwise comparisons to your analysis. To modify these lines and asterisks, just click the toolbar button once more. The results shown on the graph will automatically update if you make changes to the data or the analysis.

  • Countless Ways to Customize Your Graphs:

DraphPad Prism investigate various approaches to presenting a single dataset. Choose the visual style for your data visualization that best conveys the story it contains. Just select the desired graph type, then alter the data arrangement, data point style, labels, fonts, colors, and much more in real-time. There are countless ways to customize.

  • Explore Your Data:

Concentrate your attention on examining the most pertinent data. Tailor the way you display the connections within the data to efficiently examine sizable datasets. Have you noticed anything intriguing? To investigate the properties that correspond to a particular data point, highlight it. Prisms’ extensive data wrangling features allow you to guarantee that your analysis is founded on clean, well-structured data while also saving time.

  • Export Publication-Quality Graphs With One Click:

Cut down on the publishing time. You can modify your exports with Prism to match journal requirements in terms of file type, resolution, transparency, dimensions, and color space RGB/CMYK. Presets can help you save time.

  • Collaboration. Simplified:

To share, view, and work together on your Prism projects, use DraphPad Prism Cloud instead of those disorganized email threads. Protect your results’ reusability and interoperability by using Prism’s open access file format. You can make sure that your projects can be used outside of Prism to create new opportunities for your data workflows and integrations by using industry-standard formats (CSV, PNG, JSON, etc.).

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GraphPad Prism 10.3.1.509 Key Features:

  • Bubble Plots: Directly from the raw data, create Bubble Plots by encoding the position (X and Y coordinates), color, and size variables.
  • Violin plots: Using violin plots that are either extended or truncated, visualize distributions of large data sets.
  • Estimation Plots: Show the results of your analysis automatically
    Smoothing spline: Significant gains in the ability to display broad data trends using smoothing splines and Akima splines, with better control over the quantity of knots, or inflection points
  • Stars on Graph: Add results of multiple comparisons to graphs automatically. Select from a range of P value summary styles, such as a flexible approach suitable for any alpha level.
  • Improved Graph Customization: Create beautiful Bubble plots more quickly, simply, and intuitively than ever before. Real-time interaction and customization of graphs derived from your Multiple Variables data
  • Automatically label bar graphs: To highlight key findings in your work, annotate your bar graphs with values for the means, medians, or sample sizes.
  • Improved grouped graphs: It is simple to make graphs that display the mean (or median) and error bars in addition to individual points (scatter).
  • Greater Collaboration: To prevent those disorganized email threads, use Prism Cloud. Manage all of your conversations in one location while safely limiting who can access your work.
  • A More Open Access File Format: You can make sure that your projects can be used outside of Prism and create new opportunities for your data workflows and integrations by utilizing industry-standard formats (CSV, PNG, JSON, etc.).
  • Expanded Data Table Capabilities: As many windows as necessary can be open at once, and data can be organized into up to 2048 columns with 512 sub columns each. The expanded analysis constant dialog lets you connect to additional analysis results of all kinds.
  • Intelligent Data Wrangling: A fresh selection of tools to aid in getting your data ready for analysis. covering data tables with multiple variables, extracting and rearranging functionality, and selecting and transforming analysis
  • Hook Constant Dialog Upgrade: A practical method of creating links between various Prism elements. Every Prism analysis in the library is now covered by a new, user-friendly tree structure.
  • XY tables: Utilized when each data point has a single X and Y value that defines it. Regression models, either linear or nonlinear, are frequently used to fit this type of data.
  • Column tables: Utilized when data has been grouped according to a single grouping variable (e.g., Treatment vs. Control, Female vs. Male). frequently examined with one-way ANOVA and t tests.
  • Grouped tables: Utilized when data is grouped according to two grouping variables (e.g., male control vs. male treatment, female control vs. female treatment, etc.). frequently examined using a two-way ANOVA.
  • Contingency tables: Utilized to group count data according to two grouping variables (positive versus negative outcome and treatment versus control). suitable for Fisher’s exact test and Chi-square analysis.
  • Survival tables: Utilized in the Kaplan-Meier survival analysis process. A subject or individual with their elapsed survival time and outcome is represented by each row.
  • Parts of whole tables: When asking “What fraction of the total is each value in the table?” makes sense, use this phrase. used to create pie charts and calculate fractions.
  • Multiple variables tables: Used when the data has distinct observations for each row and distinct variables for each column that support text values. can be transformed into one of Prism’s other table types or directly analyzed using methods like Cox regression and multiple linear regression.
  • Nested tables: Utilized when groupings of data are arranged hierarchically. nested one-way ANOVA or nested t tests were used for the analysis.
  • Perform repeated measures ANOVA – even with missing data: To finish this analysis, Prism will now automatically fit a mixed effects model.
  • Perform simple and multiple logistic regression: Create a model based on one predictor variable (simple logistic regression) or several predictor variables (multiple logistic regression) and fit it to a binary outcome (yes/no, win/lose, pass/fail).
  • Principal Component Analysis (PCA): Determine which of the principal components best captures the variation in your data. Select from a variety of selection methods, such as Eigenvalue threshold, Proportion of Variance threshold, Parallel Analysis via Monte Carlo simulation, and more.
  • Multiple t test (and nonparametric) analyses: Concurrently run several independent two-sample comparison tests. Choose between parametric and nonparametric tests, and indicate if the data are paired or unpaired.
  • Analyze categorical variables with text in Multiple Linear and Multiple Logistic Regression: No coding knowledge is necessary! Prism will carry out the analysis and automatically encode categorical variables. For results that are readable and understandable, include a reference and arrange all tiers of categorical variables in a model.
  • Interpolation from multiple linear and multiple logistic regression: Using the data in the data table or the theoretical values given in the analysis, use the designated model to forecast values for the dependent variable.

Statistical Comparisons:

  • T-tests, whether paired or not. provides confidence intervals and P values.
  • Produce a volcano plot (difference versus P value) automatically based on the analysis of multiple t tests.
  • Mann-Whitney test that is nonparametric and includes the confidence interval for the median difference.
  • To compare two groups, use the Kolmogorov-Smirnov test.
  • Wilcoxon test using a median confidence interval.
  • Run numerous t tests simultaneously, selecting which comparisons are discoveries for additional research based on the False Discovery Rate (also known as Bonferroni multiple comparisons). The Tukey, Newman-Keuls, Dunnett, Bonferroni, or Holm-Sidak multiple comparison tests, the post-test for trend, or Fisher’s Least Significant tests are performed after an ordinary or repeated measures ANOVA.
  • Brown-Forsythe and Welch one-way ANOVAs without assuming populations with equal standard deviations, followed by the relevant comparison tests (Games-Howell, Tamhane T2, Dunnett T3)
    P values that have been multiplicity adjusted and confidence intervals accompany many multiple comparison tests.
  • Greenhouse-Geisser correction, which eliminates the need to assume sphericity in one-, two-, and three-way ANOVAs for repeated measures. Additionally, multiple comparison tests do not assume sphericity when this is selected.
  • Use the Friedman or Kruskal-Wallis nonparametric one-way ANOVA along with Dunn’s posttest.
  • The chi-square test or Fisher’s exact test. Determine the odds ratio and relative risk using confidence intervals.
  • Two-way ANOVA, even in cases where certain post-tests have missing values.
    repeated measures in one or both factors in a two-way ANOVA.
  • Main and simple effects are tested using multiple comparisons using Tukey, Newman-Keuls, Dunnett, Bonferroni, Holm-Sidak, or Fisher’s LSD.
  • ANOVA in three dimensions, with two levels allowed for two factors and an unlimited number of levels for the third.
  • Analysis of one-, two-, and three-way repeated measures data using a mixed effects model—a repeated measures ANOVA-like technique that can account for missing data.
  • Data from nested data tables are compared using a mixed effects model-based nested one-way ANOVA or a nested t test.

Nonlinear Regression:

  • Either enter your own equation or use one of our 105 pre-built ones. Including the exponential growth, exponential plateau, logistic, Gompertz, and beta growth and decay equations now.
  • Add implicit or differential equations.
  • For each set of data, enter a different equation.
  • Parameters for global nonlinear regression are shared across data sets.
  • robust regression without linearity.
  • Automatic detection or removal of outliers.
  • Use the extra sum-of-squares F test or AICc to compare the models.
  • Analyze parameters between datasets.
  • Put limits in place.
  • Differentially weight the points using multiple techniques, then evaluate the effectiveness of your weighting strategy.
  • You can enter your own initial estimates or accept the automatic ones.
  • Automatically create a graph curve within a given X value range.
  • Calculate the precision of the fits using the parameter’s SE or CI. Confidence intervals can be either asymmetrical, which is more accurate, or symmetrical, as is customary.
  • Calculate the imprecision’s symmetry using Hougaard’s skewness.
  • Plot prediction or confidence bands.
  • Verify the residuals’ normalcy.
  • Carries out or duplicates the model’s adequacy test.
  • Provide the dependencies or covariance matrix.
  • Interpolating points from the best fit curve is simple.
  • Determine the intersection point and both slopes of two data sets by fitting straight lines to them.

Survival Analysis:

  • Kaplan-Meier analysis of survival. Conduct nonparametric survival analysis for various groups and use the log-rank test (including the trend test) to compare the estimated survival curves for each group.
  • Regression with Cox proportional hazards. Conduct a semi-parametric survival analysis that permits the addition of covariates, or additional continuous or categorical predictor variables. Create graphs of estimated survival curves automatically for any set of values for the predictor variables.

Principal Component Analysis:

  • Selection of components using the Kaiser criterion (Eigenvalue threshold), the Proportion of Variance threshold, Parallel Analysis (Monte Carlo simulation), and other methods.
  • Scree plots, loading plots, biplots, and other graphics produced automatically.
  • Utilize the outcomes in subsequent processes such as Principal Component Analysis.

Multiple Variable Graphing:

  • Indicate the variables that define the color, size, and axis coordinates.
    Make Bubble Plots.

Column Statistics:

  • Compute the following descriptive statistics: mean, SD, skewness, kurtosis, CI, CV, min, max, quartiles, and SEM.
  • Mean or geometric mean along with the range of confidence.
  • Frequency distributions, including cumulative histograms, from bin to histogram
    Four approaches for testing normalcy (new: Anderson-Darling).
  • Probability of sampling from a normal (Gaussian) vs. lognormal distribution and the lognormality test
  • As a component of the normalcy test, create a QQ plot.
  • To compare the column, mean (or median) with a theoretical value, use a single sample t test or a Wilcoxon test.
    Use the ROUT or Grubbs method to find outliers.
  • Using the FDR method or Bonferroni multiple comparisons, analyze a stack of P values to find “significant” findings or discoveries.

Simple Linear Regression and Correlation:

  • Determine the intercept and slope using confidence intervals.
  • Push the regression line through a predetermined intersection.
  • Fit to mean Y or replicate Y values.
  • A runs test can be used to check for deviations from linearity.
  • Compute residuals and plot them using four different methods (including the QQ plot).
  • Examine the intercepts and slopes of two or more regression lines.
  • New points should be interpolated along the standard curve.
  • Nonparametric correlation, such as Pearson or Spearman.

Generalized Linear Models (GLMs)

  • Using the newly created multiple variables data table, create models that relate several independent
  • Variables to a single dependent variable.
  • When Y is continuous, multiple linear regression is used.
  • Poisson regression (when Y is counts; 0, 1, 2, …).
  • When Y is binary—yes/no, pass/fail, etc.—logistic regression is used.

Diagnostic (Clinical) Laboratory Statistics

  • Plots of Bland and Altman.
  • Curves of receiver operator characteristic (ROC).
  • Deming regression, also known as type Ill linear regression.

Simulations:

  • Run XY, Column, or Contingency table simulations.
  • Monte-Carlo analysis of repeated simulations of data.
  • Plot functions using selected or entered equations with user-specified parameter values.

Other Calculations:

  • Confidence interval and area under the curve.
  • Change data.
  • Establish normalcy.
  • Determine the outliers.
  • Tests for normalcy.
  • Flip the tables.
  • Baseline subtracted (columns combined).
  • Calculate each value as a percentage of the row, column, or overall sum.

GraphPad Prism 10.3.1.509 Changelog:

(Released on 28-08-2024)

Analysis Bug Fixes:

  • Fixed an issue in which Prism would crash while performing an Unpaired t test from a grouped data table with error values and data that contained several data sets.
  • Fixed an issue in which blank results were incorrectly displayed in the Outliers tab of the Nonlinear Regression analysis after adding empty data sets to the data table.

Graphing Bug Fixes:

  • (Mac) Fixed the issue in which the area fill of XY graphs appeared corrupted if some points were out of the Y-axis limits.
  • (Mac) Fixed the issue in which unexpected data points appeared on Interleaved bar graphs for which symbols were enabled.

Other Bug Fixes:

  • Fixed the issue in which it was impossible to open flies with undefined parameters for disabled transforms.
  • Fixed the “hierarchical clustering” link in the Dendrogram section of the Format Graph dialog.
  • (Windows) Fixed the issue in which Prism would crash while performing the undo action to revert the magic operation for a graph with CLD labels and a non-default color scheme.
  • (Windows) Fixed the issue in which Prism would crash while typing text over the existing text of floating notes.
  • (Mac) Fixed the issue in which Prism would crash while switching to the Dendrogram tab of the Format Graph dialog if previously the Dendrogram data object was disabled for the default Dendrogram graph from Hierarchical Clustering and the graph type was changed to Heatmap using the Change Graph Type dialog.
  • (Mac) Fixed the issue in which Prism would crash while changing the orientation of a dendrogram created for the hierarchical clustering sample data.

Screenshot:

GraphPad-Prism-Full-Download

GraphPad-Prism-Free-full-Download

Instruction install & activate:
  • Disconnect from the internet (Recommended).
  • Extract and install GraphPad Prism 10.3.1.509 by using setup.
  • After the installation, don’t the program or exit if running.
  • Copy the Fix file to the installation directory and replace it.
  • It’s done, Enjoy GraphPad Prism 10.3.1.509 Full Version.

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