With StatPlus, one gets a robust suite of statistics tools and graphical analysis methods that are easily accessed through a simple and straightforward interface. The range of possible applications of StatPlus is virtually unlimited - sociology, financial analysis, biostatistics, economics, insurance industry, healthcare and clinical research - to name just a few fields where the program is already being extensively used.
- G Power Analysis Tool For Mac Os
- G Power Analysis Tool For Mac Download
- G Power Analysis Tool For Mac Shortcut
While StatPlus is a professional statistical analysis tool, the interface is so simple that even people who have no knowledge of statistics are capable of processing data, provided they know how to use PC and clear instructions are given. This frees up intellectual resources for analyzing the results, rather than agonizing over who and how processed the data, and if any mistakes were made in the process.
This video illustrates how to calculate power for a Pearson correlation coefficient. We look at the sample size required to get a desired power level (.80 is.
Powerful Spreadsheet
Standalone version reads numerous text formats, Microsoft* Excel* 97-2003 (XLS) and 2007-2019 (XLSX) workbooks, SPSS* Documents (up to v22) and supports almost all Excel built-in worksheet functions (math, statistical, financial). StatPlus comes with Excel add-in (StatFi) that transforms Excel into a statistical software package.Version 5 includes own chart engine (histograms, bars, areas, point-graphs, pies, statistical charts, control charts) and reads StatSoft* Statistica* documents.
Cycling Analytics is a powerful and flexible analysis tool for both coaches and athletes. As a keen cyclist it allows me to track my performance, and drill down into specifics if I need to. As a coach it allows me to organise and plan for my athletes, enabling them to reach their potential as cyclists. Power Analysis for ANOVA: Small Effect Size A power analysis was conducted to determine the number of participants needed in this study (Cohen, 1988). The α for the ANOVA will be set at.05. To achieve power of.80 and a small effect size (f² =.10), a total sample size of 969 is required to detect a significant model (F (2, 966) = 3.00). G.Power Overview. G.Power is a statistical power analysis program designed to analyze different types of power and compute size with graphics options. It covers many different statistical tests of the F, t, chi-square, and z test families as well as some exact tests. G.Power provides improved effect size calculators and graphics options, it supports both a distribution-based and a design-based input mode, and it offers five different types of power analyses.
Buy It Now or Try It For Free
Statistics A-Z
StatPlus allows to perform various forms of analysis - from data transformation and sampling to complex analysis, including as non-parametric and regression analysis, survival analysis, and a wide variety of other methods.
Multi-platform
StatPlus is available for both PC and Mac platforms at no extra charge. Both versions include standalone spreadsheet and Excel add-in. Save learning time and costs for your mixed PC and Mac environment.
Free Trial
We have free trial that gives you an opportunity to evaluate the software before you purchase it. Should you have any questions during the trial period, please feel free to contact our Support Team.
Affordable
You will benefit from the reduced learning curve and attractive pricing while enjoying the benefits of precise routines and calculations. Mac/PC license is permanent, there is no renewal charges.
Requirements
StatPlus requires Windows 2000 or newer, Windows 7 or newer recommended. Excel add-in (StatFi) requires Excel 2007 or newer. StatPlus supports Windows 10 and Excel 2019.
G Power Analysis Tool For Mac Os
StatPlus and StatFi Features List
- Pro Features
- Fast and powerful standalone spreadsheet.
- Add-in for Excel 2007, 2010, 2013, 2016 and 2019.
- Priority support.
- Permanent license with free major upgrades during the maintenance period.
- Options to emulate Excel Analysis ToolPak results and migration guide for users switching from Analysis ToolPak.
- Basic Statistics
- Detailed descriptive statistics.
- One-sample t-test.
- Two-sample t-test.
- Two-sample t-test for summarized data.
- Fisher F-test.
- One-sample and two-sample z-tests.
- Correlation analysis and covariance.
- Normality tests (Jarque-Bera, Shapiro-Wilk, Shapiro-Francia, Cramer-von Mises, Anderson-Darling, Kolmogorov-Smirnov, D'Agostino's tests).
- Cross-tabulation and Chi-square.
- Frequency tables analysis (for discrete and continuous variables).
- Multiple definitions for computing quantile statistics.
- Analysis of Variance (ANOVA)
- One-way and two-way ANOVA (with and without replications).
- Three-way analysis of variance.
- Post-hoc comparisons - Bonferroni, Tukey-Kramer, Tukey B, Tukey HSD, Neuman-Keuls, Dunnett.
- General Linear Models (GLM) ANOVA.
- Within subjects ANOVA and mixed models.
- Multivariate Analysis
- Principal component analysis (PCA).
- Factor analysis (FA).
- Discriminant function analysis.
- Nonparametric Statistics
- 2x2 tables analysis (Chi-square, Yates Chi-square, Exact Fisher Test, etc.).
- Rank and percentile.
- Chi-square test.
- Rank correlations (Kendall Tau, Spearman R, Gamma, Fechner).
- Comparing independent samples
Mann-Whitney U Test, Kolmogorov-Smirnov test, Wald-Wolfowitz Runs Test, Rosenbaum Criterion. Kruskal-Wallis ANOVA and Median test. - Comparing dependent samples
Wilcoxon Matched Pairs Test, Sign Test, Friedman ANOVA, Kendall's W (coefficient of concordance). - Cochran's Q Test.
- Regression Analysis
- Multivariate linear regression (residuals analysis, collinearity diagnostics, confidence and prediction bands).
- Weighted least squares (WLS) regression.
- Logistic regression.
- Stepwise (forward and backward) regression.
- Polynomial regression.
- Curve fitting.
- Tests for heteroscedasticity: Breusch–Pagan test (BPG), Harvey test, Glejser test, Engle's ARCH test (Lagrange multiplier) and White test.
- Time Series Analysis
- Data processing.
- Fourier analysis.
- Smoothing.
- Moving average.
- Analysis.
- Autocorrelation (ACF and PACF).
- Interrupted time series analysis.
- Unit root tests - Dickey–Fuller, Augmented Dickey–Fuller (ADF test), Phillips–Perron (PP test), Kwiatkowski–Phillips–Schmidt–Shin (KPSS test).
- Survival Analysis
- Life tables.
- Kaplan-Meier (log rank test, hazard ratios).
- Cox proportional-hazards regression.
- Probit-analysis (Finney and LPM).
LD values (LD50/ED50 and others), cumulative coefficient calculation. - Receiver operating characteristic curves analysis (ROC analysis).
AUC methods - DeLong's, Hanley and McNeil's. Report includes: AUC (with confidence intervals), curve coordinates, performance indicators - sensitivity and specificity (with confidence intervals), accuracy, positive and negative predictive values, Youden's J (Youden's index), Precision-Recall plot. - Comparing ROC curves.
- Data Processing
- Sampling (random, periodic, conditional).
- Random numbers generation.
- Standardization.
- Stack/unstack operations.
- Matrix operations.
- Statistical Charts
- Histogram
- Scatterplot.
- Box plot.
- Stem-and-leaf plot.
- Bland-Altman plot.
- Bland-Altman plot with multiple measurements per subject.
- Quantile-quantile Q-Q plots for different distributions.
- Control charts - X-bar, R-chart, S-chart, IMR-chart, P-chart, C-chart, U-chart, CUSUM-chart.
G Power Analysis Tool For Mac Download
Data analysis software for Mac and Windows
JMP is the data analysis tool of choice for hundreds of thousands of scientists, engineers and other data explorers worldwide. Users leverage powerful statistical and analytic capabilities in JMP to discover the unexpected.
Explore data more fully with powerful statistics
JMP helps you tackle your routine and difficult statistical problems. From easily accessing your data from various sources, to using quick, reliable data preparation tools, and performing choice statistical analyses, JMP lets you get the most out of your data in any situation.
Discover meaningful findings by digging deeper into your data
You’ve done some exploration of your data. Now, you’re ready to ask more questions and make new discoveries. With its linked analyses and graphics, JMP is the ideal data analysis tool for understanding complex relationships, digging deeper, discovering the unexpected.
Share new discoveries with interactive visualization
G Power Analysis Tool For Mac Shortcut
Discoveries are meant to be seen. Move effortlessly from discovery to sharing with the data visualization capabilities in JMP. Tell the story of your findings with interactive dashboards and web visualizations.