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.
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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. 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. 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.
The R Project for Statistical Computing
Start Free 30 Day Trial. No credit card required. 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. When this is chosen, multiple comparison tests also do not assume sphericity. Fisher's exact test or the chi-square test. Calculate the relative risk and odds ratio with confidence intervals. 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 built-in equations, or enter your own. Now including family of growth equations: 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.
Statistics the Mac Way | AnalystSoft | StatPlus:mac | StatPlus | BioStat | StatFi
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. 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: Mean or geometric mean with confidence intervals. Frequency distributions bin to histogram , including cumulative histograms. Normality testing by four methods new: Lognormality test and likelihood of sampling from normal Gaussian vs. 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. 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.
Comments on STATISTICA
Pearson or Spearman nonparametric correlation. Multiple linear regression including Poisson regression using the new multiple variables data table. Receiver operator characteristic ROC curves. In , the Macintosh version of Statistica was released. Statistica 5. It featured many new statistics and graphics procedures, a word-processor-style output editor combining tables and graphs , and a built-in development environment that enabled the user to easily design new procedures e. In , Statistica 6 was based on the COM architecture and it included multithreading and support for distributed computing.
Statistica 10 was released in November This release featured further performance optimizations for the bit CPU architecture, as well as multithreading technologies, integration with Microsoft Sharepoint , Microsoft Office and other applications, the ability to generate Java and C code, and other GUI and kernel improvements. Statistica 12 was released in April and features a new GUI, performance improvements when handling large amounts of data, a new visual analytic workspace, a new database query tool as well as several analytics enhancements.
List of releases: Statistica includes analytic and exploratory graphs in addition to standard 2- and 3-dimensional graphs.
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Brushing actions interactive labeling, marking, and data exclusion allow for investigation of outliers and exploratory data analysis. Operation of the software typically involves loading a table of data and applying statistical functions from pull-down menus or in versions starting from 9.
The menus then prompt for the variables to be included and the type of analysis required. It is not necessary to type command prompts.