Question

Match the following statistical tests with the level of measurement or other requirement required for each analysis.

Pearson r

      [ Choose ]            Ordinal, very small group size            Interval or ratio data            Ordinal data            Nominal data      

Spearman 's Rank Order (rho)

      [ Choose ]            Ordinal, very small group size            Interval or ratio data            Ordinal data            Nominal data      

Kendall's Tau

      [ Choose ]            Ordinal, very small group size            Interval or ratio data            Ordinal data            Nominal data      

Chi Square

      [ Choose ]            Ordinal, very small group size            Interval or ratio data            Ordinal data            Nominal data      

Answer 1

Levels of measurement are:

Nominal (Categorical)- Lowest on scale data organized into categories only
Ordinal- Categories which can be ordered by rank, but intervals between numbers are not truly equal
Interval- Distances between scale are equal, however, 0 does not mean the absence of the concept
Ratio- Highest form of measurement, equal distance between points on scale and a zero means absence of concept

So, the answers will be:

Pearson r Interval or ratio data

When one variable increases do another variable significantly increase or decrease, common statistical test when the researcher wants to examine whether there is a linear relationship between two variables measured at an interval or ratio level.

Spearman 's Rank Order (rho) Ordinal data  

Spearman's correlation is a nonparametric measure of the strength and direction of association that exists between two variables measured on at least an ordinal scale.

Kendall's Tau Ordinal, very small group size  

Usually smaller values than Spearman’s rho correlation. Calculations based on concordant and discordant pairs. P values are more accurate with smaller sample sizes.

Chi-Square Nominal data   

Use with nominal (Categorical/ discrete) data, a nonparametric test, Used to examine if there is a relationship between two categorical variables, Tests for differences between frequencies expected if groups are alike and frequencies actually observed in the data