Usage Notes

Much of what is considered nonparametric kTrendsTest statistics is included in other chapters. Topics of possible interest in other chapters are: nonparametric measures of location and scale (Chapter 1, Basic Statistics), nonparametric measures in a contingency table (Chapter 5, Categorical and Discrete Data Analysis), measures of correlation in a contingency table (Chapter 3, Correlation and Covariance), and tests of goodness of fit and randomness (Chapter 7, Tests of Goodness of Fit).

Missing Values

Most routines described in this chapter automatically handle missing values (NaN, “Not a Number”; see the Missing Values of this manual).

Tied Observations

Many of the routines described in this chapter contain an argument fuzz in the input. Observations that are within fuzz of each other in absolute value are said to be tied. Moreover, in some routines, an observation within fuzz of some value is said to be equal to that value. In routine wilcoxonSignRank, for example, such observations are eliminated from the analysis. If fuzz = 0.0, observations must be identically equal before they are considered to be tied. Other positive values of fuzz allow for numerical imprecision or roundoff error.