The correct option is A.
When the data are nominal or ordinal.
<h3>What are the Types of correlation?</h3>
There are three types of correlation:
1. Positive and negative correlation
2. Linear and non-linear correlation
3. Simple, multiple, and partial correlation
<h3>According to the information:</h3>
There are different types of correlation one can use based on the types of variables being examined.
Spearman’s rho is a superb choice when you have nominal or ordinal data because Pearson’s isn't appropriate. Ordinal data have a minimum of three categories and the categories have a natural order. for instance , first, second, and third during a race are ordinal data.
<h3>Briefing:</h3>
Two variables can have some quite relationship, i.e., change in one may cause a change within the other.
If a change within the value of one variable causes a simultaneous change in the other variable in the same or opposite direction, then it’s termed as correlation, or these variables are said to be correlated. Keeping these in mind the answer to this question is When the data are nominal or ordinal
When the data are nominal or ordinal.
So the option no A is correct.
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I understand that the question you are looking for is:
There are different types of correlation one can use based on the types of variables being examined. When conducting an analysis, when do you need to use spearman’s rho instead of Pearson's r ?
A. When the data are nominal or ordinal.
B. When the data are ratio or interval.
C. When the data are random.
D. Spearman's rho should never be used for correlations.
