We use a two-sample version this test now for our non-parametric paired t-test and a one-sample version can be implemented in a similar way. A rank-based test designed for this purpose is the (two-sided) Wilcoxon Signed Rank Test. Thus, using our sampled data, we want to test the null hypothesis that the median of a population is equal to some specified value. For this purpose, the median of the population, rather than the mean, is the value we will test since it is more robust to sampling errors. This leads us to a non-parametric version of the one-sample t-test.Ĭomputational Method - The idea is to provide a procedure, valid over a wide range of distributions, for testing a value that measures the central tendency of the population. Although this test is known to be quite robust, it can still lead to misleading results if this assumption is not satisfied. The only assumption made in using the one-sample t-test is that the sampled population has a normal distribution. These differences form a single group which is analyzed with a one-sample t-test to see if they are sampled from a population with zero mean. In performing a paired t-test, the difference between the measurements of the two groups is computed for each subject. One application of this test is the paired t-test, the simplest design for repeated measures. The value of the hypothesized mean is specified in the Test Options dialog. The One-Sample Signed Rank Test tests the hypothesis that the median of a population equals a specified value.įeature Description – The one-sample t-test offered in SigmaPlot uses a single group of sampled data to test the null hypothesis that the mean of a population has a specified value. Improved accuracy in multiple comparison statistics for higher-order effects in 3-Way ANOVA reports.Įnhancements to Existing Features One-Sample Signed Rank Test.P-values added for Dunnett’s and Duncan’s multiple comparison procedures.More accurate statistical errors in nonlinear regression reports for fit models with equality constraints.Bland-Altman graph and statistics for method comparison.Parallel line analysis to determine if linear regression slopes and intercepts are different.Normal distribution comparison with graph and statistics for preliminary quality control analysis.However, SigmaPlot will check if your data set meets test criteria and if not, it will suggest what test to run. If underlying assumptions are not met, you may be given inaccurate or inappropriate results without knowing it. Each statistical analysis has certain assumptions that have to met by a data set.
#Morrison equation sigmaplot software software#
This wizard-based statistical software package guides users through every step and performs powerful statistical analysis without having to be a statistical expert. The statistical functionality was designed with the non-statistician user in mind. SigmaPlot is now bundled with SigmaStat as an easy-to-use package for complete graphing and data analysis.
SigmaPlot Has Extensive Statistical Analysis Features