Summary of Statistical Tests
Note that not all tests listed in the table are covered in this course. The one's that are covered are linked to the appropriate material in the course.
This table can help you decide when to use which statistic. The first issue is the level of measurement of the data. The next issue is whether we are trying to assess causal relationships, or do we just want to measure the strength and direction of a relationship. If the experimental approach is taken then we need to look very carefully at the characteristics of the sample for all independent variables (IVs).
Level of Meas urement 
Sample Characteristics  Corr ela tion 


1 Sample 
2Sample  KSample (i.e., >2) 

Indep endent 
Dependent  Indep endent 
Dependent  
Categorical or Nominal 
x^{2} or Binomial 
x^{2} 
Macnamar's x^{2} 
x^{2} 
Cochran's Q 

Rank or Ordinal 
Mann Whitney U 
Wilcoxin Matched Pairs Signed Ranks 
Kruskal Wallis H 
Friedman's ANOVA 
Spear man's rho 

Parametric (Interval & Ratio) 
z test or t test 
t test between groups 
t test within groups 
1way ANOVA between groups 
1way ANOVA (within or repeated measure) 
Pear son's r 
Factorial (2way) ANOVA can handle more than 1 IV 