Location test
location test, location test instructions ovulationA location test is a statistical hypothesis test that compares the location parameter of a statistical population to a given constant, or that compares the location parameters of two statistical populations to each other Most commonly, the location parameter or parameters of interest are expected values, but location tests based on medians or other measures of location are also used
Onesided location test
The onesided location test compares the location parameter of one sample to a given constant An example of a onesample location test would be a comparison of the location parameter for the blood pressure distribution of a population to a given reference value In a onesided test, it is stated before the analysis is carried out that it is only of interest if the location parameter is either larger than, or smaller than the given constant, whereas in a twosided test, a difference in either direction is of interest
Twosided location test
The twosided location test compares the location parameters of two samples to each other A common situation is where the two populations correspond to research subjects who have been treated with two different treatments one of them possibly being a control or placebo In this case, the goal is to assess whether one of the treatments typically yields a better response than the other In a onesided test, it is stated before the analysis is carried out that it is only of interest if a particular treatment yields the better responses, whereas in a twosided test, it is of interest whether either of the treatments is superior to the other
The following tables provide guidance to the selection of the proper parametric or nonparametric statistical tests for a given data set
Parametric and nonparametric location tests
The following table summarizes some common parametric and nonparametric tests for the means of one or more samples
Ordinal and numerical measures1 group  N ≥ 30  Onesample ttest  
N < 30  Normally distributed  Onesample ttest  
Not normal  Sign test  
2 groups  Independent  N ≥ 30  ttest  
N < 30  Normally distributed  ttest  
Not normal  Mann–Whitney U or Wilcoxon ranksum test  
Paired  N ≥ 30  paired ttest  
N < 30  Normally distributed  paired ttest  
Not normal  Wilcoxon signedrank test  
3 or more groups  Independent  Normally distributed  1 factor  One way anova 
≥ 2 factors  two or other anova  
Not normal  Kruskal–Wallis oneway analysis of variance by ranks  
Dependent  Normally distributed  Repeated measures anova  
Not normal  Friedman twoway analysis of variance by ranks 
1 group  np and n1p ≥ 5  Zapproximation  
np or n1p < 5  binomial  
2 groups  Independent  np < 5  fisher exact test or Barnard's test 
np ≥ 5  chisquared test  
Paired  McNemar or Kappa  
3 or more groups  Independent  np < 5  collapse categories for chisquared test 
np ≥ 5  chisquared test  
Dependent  Cochran´s Q 
 

 
 
 
 
 
 
 

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29.10.2014
Location test
Location test
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