Search results
Results from the WOW.Com Content Network
The use of Q–Q plots to compare two samples of data can be viewed as a non-parametric approach to comparing their underlying distributions. A Q–Q plot is generally more diagnostic than comparing the samples' histograms, but is less widely known. Q–Q plots are commonly used to compare a data set to a theoretical model.
The following tables compare general and technical information for a number of statistical analysis packages. ... Data processing Base stat. [Note 2] Normality ...
General numerical computing package with many extension modules. Syntax mostly compatible with MATLAB IGOR Pro: WaveMetrics 1986 1988 8.00 May 22, 2018: $995 (commercial) $225 upgrade, $499 (academic) $175 upgrade, $85 (student) Proprietary: interactive graphics, programmable, 2D/3D, used for science and engineering, large data sets. J ...
Dunnett's test's calculation is a procedure that is based on calculating confidence statements about the true or the expected values of the differences ¯ ¯, thus the differences between treatment groups' mean and control group's mean.
Plotly – plotting library and styling interface for analyzing data and creating browser-based graphs. Available for R, Python, MATLAB, Julia, and Perl; Primer-E Primer – environmental and ecological specific; PV-WAVE – programming language comprehensive data analysis and visualization with IMSL statistical package
A paired difference test is designed for situations where there is dependence between pairs of measurements (in which case a test designed for comparing two independent samples would not be appropriate). That applies in a within-subjects study design, i.e., in a study where the same set of subjects undergo both of the conditions being compared.
Get answers to your AOL Mail, login, Desktop Gold, AOL app, password and subscription questions. Find the support options to contact customer care by email, chat, or phone number.
In statistics, multiple correspondence analysis (MCA) is a data analysis technique for nominal categorical data, used to detect and represent underlying structures in a data set. It does this by representing data as points in a low-dimensional Euclidean space. The procedure thus appears to be the counterpart of principal component analysis for ...