Statistics software GSS
GSS is statistics software for scientists, developed specifically to help users rapidly identify the correct statistical analysis. GSS stands for “Guided Statistics for Scientists”. GSS has a particularly powerful module for dose response analysis.
It can be intimidating to read across statistical text books, trying to find the correct statistical analysis for a study. And since statistics is such a large field, it is often difficult to understand when to use which analysis or test. We understand that scientists want to conduct appropriate statistics, but their focus is science and not statistics. Therefore, we developed GSS, a statistical software and support system, which helps scientists to quickly find and conduct the correct analyses. I.e. GSS is a guided statistical software system, that accompanies you during your analysis, step by step. Nevertheless, GSS is a powerful software with professional capabilities, offering many advanced options offered as expert settings when needed.
Features
Desciptive statistics
Descriptive statistics are used to summarize or describe measured values. GSS provides a range of descriptive statistics, such as mean, median, mode, geometric mean, standard deviation, variance, standard error and many more.
- Sample size
- Sum
- Mean
- Median
- Mode
- Geometric mean
- Harmonic mean
- Standard deviation
- Variance
- Standard error
- Percentiles
- Confidence intervals
Statistical hypothesis testing
GSS includes a powerful module for statistical testing, which was designed to make test selection an intuitive process. In addition, it is very comprehensive, includes all standard tests and also many tests that are not often found in other statistical software. For an easy start into statistical hypothesis testing, GSS supports various ways to enter data. Hence there is no need for previous data processing or formatting.
The intuitive user interface then provides step by step guidance through the data analyses, allowing even those with less experience to easily find the right statistical tests for the given datatype and purpose. For any remaining uncertainties a built-in statistical guide and comprehensive help is available. In short, GSS helps anyone to understand the statistical background of the tests available and on how to interpret results.
Hypothesis tests for one group
- One-sample-t-test
- One-sample Kolmogorov-Smirnov test
- One-sample-sign-test
- Shapiro-Wilk test
Hypothesis tests for two groups
- Two-sample-t-test (incl. Min. detectable difference, MDD)
- Paired t-test
- F-test/Bartlett-test
- Welch-test
- Mann-Whitney-U-test (incl. Min. detectable difference, MDD)
- Wilcoxon-signed-rank-test
- Two-sample Kolmogorov-Smirnov test
- Moods median-test
- Paired sign-test
- McNemar-test
- Chi-squared-test
- Fisher’s exact test
Hypothesis tests for more than two groups
- ANOVA
- Repeated measures ANOVA
- Bartlett-test
- Jonckheere’s trend test
- Kruskal-Wallis-test
- Moods median-test
- Levene-test
- Brown-Forsythe-test
- Mauchy-test
- Friedman-test
- Quade-test
- Cochran’s Q-test
- CPCAT
Correlations
- Pearson correlation coefficient test
- Spearman’s rank correlation coefficient
- Kendal rank correlation coefficient (tau-b) test
- Kendal rank correlation coefficient (tau-c) test
Power analysis
- for t-test
Dose-response analyses
All versions of GSS include a very powerful module for dose-response analysis. GSS offers a variety of mathematical functions which can be fitted to the measured data to find the best possible description of the dose-response relationship. Various goodness-of-fit measures are therefore available to justify the selection of a fitted function. In addition, confidence limits and confidence bands are provided to assess the uncertainty of an estimated parameter and of the uncertainty of the dose-response relationship. GSS-DR additionally includes model averaging and the calculation of confidence bands.
Dose-response analyses
- Null model
- Standard functions for continuous data (Horizontal line, Exponential 3, Exponential 5, Hill 3, Hill 5, Inv. Exp. 3, Inv. Exp. 5, LN family 3, LN family 5)
- Standard functions for quantal data (Logistic, Probit, Log Logistic, Log Probit, Weibull, gamma, Linearized one stage, Linearized two stages, Linearized three stage)
- General dose-response analysis for stimulation and inhibition (Universal Hill equation)
- Receptor binding (Non-specific saturation binding, Specific saturation binding, Sigmoidal specific saturation binding)
- Enzyme kinetics (Michaelis-Menten, Sigmoidal velocity, Inhibitor-induced inhibition, Substrate-induced inhibition)
- Various goodness-of-fit-measures (R², adjusted R², NRMSE, AIC, AICc, BIC, Chi²)
- ECx and ICx calculation
- Outlier test (Grubb’ test)
- Options for automatic data transformation
- Wilson scores for quantal data
Distribution fitting and curve fitting
Distribution fitting is an essential part of many statistical analyses, because without knowing how your data is distributed it may be difficult to find an adequate statistical test for your data. In case you are in doubt about the distribution of the data, you can use the distribution fitting tool implemented in GSS.
Also, a curve fitting tool is included in GSS, which helps you to describe relationships or to assess correlations. In order to determine which function best describes your data, GSS calculates various goodness of fit measures. In addition, several correlations tests can be conducted, including Pearson, Spearman, Kendall’s (tau-b and tau-c) or Somer’s measure of association.
Distribution fitting
- Probability density/mass function (Binomial, Poisson, Geometric, Uniform, Normal, Log-normal, Exponential, Gamma, Weibull, Beta, Logistic, Extreme)
- Cumulative distribution function (Binomial, Poisson, Geometric, Uniform, Normal, Log-normal, Exponential, Gamma, Weibull, Beta, Logistic, Extreme)
Curve fitting
- Standard functions
- Dynamic growth functions
- Periodic functions
- Kinetic functions
Powerful scientific charts
For the visualisation of your data GSS includes a powerful chart building tool, designed to produce clean graphs suitable for scientific publications. Furthermore, there are many options to customise graphs and to save your favourite chart designs for future use. The chart designer also includes a functionality for adding curve fits to your charts.
Scientific charts
- Scatter plot
- Line plot
- Bar plot
- Box plot
- Area plot
- Histogram plot
- Error bar plot
- High-low plot
- Horizontal bar plot
- Pie plot
- Stacked bar plot
- Stacked area plot
- Stacked percent bar plot
- Stacked percent area plot
Reporting
While conducting statistical analyses you can add all your results (or just the ones you need) to a report. A report is a text document, which can include results, tables and graphs of your statistical analyses. You can modify a report freely or you can add additional explanations as needed. This report can be the basis for your next publication.
Ready for your first analysis?
Start your data analysis now and experience how easy statistics can be. Whether for studies, research or professional projects – GSS supports you with innovative tools and an intuitive user interface.
