The Statistics package provides various parametric and non-parametric tools for performing hypothesis testing and statistical inference.
apply the chi-square test for goodness-of-fit
apply the chi-square test for independence in a matrix
apply the chi-square suitable model test
apply the one sample chi-square test for the population standard deviation
apply the one sample t-test for the population mean
apply the one sample z-test for the population mean
apply Shapiro and Wilk's W-test for normality
apply the two sample F-test for population variances
apply the paired t-test for population means
apply the two sample t-test for population means
apply the two sample z-test for population means
All tests generate a complete report of all calculations in the form of a userinfo message. In order to access these reports when applying tests, specify infolevel[Statistics] := 1 or use the summarize option.
Build a sample from a Rayleigh distribution and compare with the population mean and population standard deviation.
S ≔ Sample⁡Rayleigh⁡7,100:
Test that the sample S is drawn from a population with mean equal to 8 and standard deviation equal to 5.
Test that the sample S is drawn from a population with mean equal to 8 with unknown standard deviation.
Test that S is drawn from a normal distribution and return an embedded report.
Sample drawn from a population that follows a normal distribution
Sample drawn from population that does not follow a normal distribution
Rejected: This statistical test provides evidence that the null hypothesis is false.
Test that Normal(8.77,4.59) is a suitable model for the population of S.
Test for independence in a 3x2 table.
X ≔ Matrix⁡32.,12.,14.,22.,6.,9.:
Return a report for the test above:
Chi-Square Test for Independence
Two attributes within a population are independent of one another
Two attributes within a population are not independent of one another
Total Elements: 95
Computed Statistic: 10.71219801
Computed p-value: .00471928013399603
Critical Values: 5.99146454710798
This statistical test provides evidence that the null hypothesis is false.
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