Compute the F-value for an analysis of variance (ANOVA) study, given the between-groups (or treatment) mean square value, and the within-groups (or residual / error) mean square value. Knowing the F-value associated with an analysis of variance is critical to assessing hypotheses and comparing models in analytics studies that rely on ANOVA methods.
Compute the critical value for the F-distribution, given the probability level, and the numerator and denominator degrees of freedom. Knowing the F-value for a particular probability level is often very useful in analytics.
Compute the cumulative distribution function (CDF) for the F-distribution, given the upper limit of integration x, and the numerator and denominator degrees of freedom. The F-distribution CDF yields the area under the F-distribution from 0 to x, which is very useful for assessing probabilities in analytics studies that rely on F-tests.
Compute the probability density function (PDF) for the F-distribution, given the point at which to evaluate the function x, and the numerator and denominator degrees of freedom. The F-distribution PDF is very useful for identifying critical values and assessing probabilities in analytics studies that rely on F-tests.
Compute the expected value (that is, the mean) for a random variable from the F-distribution, given the denominator degrees of freedom. Knowing the expected value for an F-distribution random variable can be very useful in analytics studies that rely on F-tests.
Compute the variance for a random variable from the F-distribution, given the numerator degrees of freedom and the denominator degrees of freedom. Knowing the variance for an F-distribution random variable can be very useful in analytics studies that rely on F-tests.
Compute the probability value for an F-test, given the F-value, and the numerator and denominator degrees of freedom. Knowing the probability level associated with a particular F-value is often very useful for making decisions about the value of statistical models in analytics studies.
Compute the F-value for a hierarchical multiple regression study, given an R-square value for a set of predictor variables A, an R-square value for the sum of A and another set of predictor variables B, the number of predictors in sets A and B, and the total sample size. The calculator computes the F-value associated with the addition of set B, which can provide useful insights for analytics studies that rely on hierarchical regression.
Compute the F-value and associated p-value for a multiple regression study, given the model R-square, the number of predictor variables, and the total sample size. F and p-values can be very useful ways of assessing and comparing different regression models when performing analytics.
Compute the noncentral F-distribution's cumulative distribution function (CDF), given an F-value, the numerator and denominator degrees of freedom, and the noncentrality parameter. The noncentral F-distribution is one of the foundational statistical distributions used in analytics.