Parametric VERSUS Non Parametric test BY JWANIKA VANSIYA
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Parametric VERSUS
Non Parametric test
BY JWANIKA VANSIYA
Parametric test
• A statistical test, in which specific assumptions are made about the population parameter is known as parametric test.
Parametric test
When to use parametric test?
Four conditions have to be satisfied:
Data must be interval/ ratio
•
Subjects should be randomly selected
When to use parametric test ????
.Data should be normally distributed.
.
Variation in the results should be roughly same..• Homogenecity of variances assessed by
Levene’s test
Non parametric test
• Nonparametric tests are also called distribution-free tests because they don’t assume that your data follow a specific distribution.
Non parametric test
When to use non parametric test?
• Nominal or ordinal data
1
• Non normal distribution of data2
Parametric test or Non parametric test-Determination
Parametric versus Non Parametric test.
Parametric test
Specific assumptions are made regarding the population
Parametric test is powerful if it is exists
Test statistics based on distribution
Non parametric test
No specific assumptions are made regarding the population
Not powerful like parametric test
Test statistics is arbitrary
.Parametric test
No parametric test exists for nominal scale data
Central measure - mean
Can draw more conclusions
Non parametric test
Non parametric test exists for nominal scale data
Central measure - median
Simplicity , not affected by outliers
Parametric versus non parametric testStudy type Parametric test Non parametric testCompare means between two distinct/independent groups
Two-sample t-test Mann- whitney test
Compare two quantitative measurements taken from the same individual
Paired t-test Wilcoxon signed-rank test
Compare means between three or more distinct/independent groups
Analysis of variance (ANOVA)
Kruskal-Wallis test
Study type Parametric test Non parametric test
Repeated measures, >2 conditions
One-way, repeated measures ANOVA Friedman's test
Estimate the degree of association between two
quantitative variables Pearson coefficient of correlation
Spearman’s rank correlation
Thank you
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