Topic 0009: N24 vs Correlation

Is it possible for me to execute correlation with a sample n=24 to see the relationship between variables? Here are some answer guide me as well;



Eddie Seva See (Bicol University)

Hi Syamsul Nor Azlan Mohamad, correlations are characterized by strength (magnitude), and if a random sample, by significance. Not by reliability. To calculate the magnitude, 3 samples would be mathematically sufficient. But for a very small sample size, a very strong magnitude would more likely still result to a non-significant relationship. On the other hand, in a very large sample size, a very low magnitude may still result to a significant relationship. For a sample size of 24, t-test of r ( which is parametric), is used to determine significance of relationship.

Adel Al Sharkasi (University of Benghazi, Faculty of Science)

Statistically, you can calculate the correlation for data of size 24 or less but the question is how to calculate it as the method of calculation depends on the type of data (quantitative or qualitative).

However, if you want to test whether or not the correlation is the significant, you need to worry about the normality of your data and the size. In your situation as you mention that N=24 is population so you do not worry about the size of population and you can calculate any parameter using tools of descriptive statistics not inferential statistics

Benjamin Chris Ampimah (Jiangsu University)


Yes it is possible to compute correlation for a sample of size 24. A scatter plot give you a rough and fair idea of the the relationship between the variables. this you can see pictorially. Since correlation talks about the relationship between variables, it beholds on you to go a step further to ascertain the predictive power of your independent variable(s) by computing the coefficient of determination. This helps you to know know the extent to which the independent variable can explain or predict your dependent various. You can compute this by squaring the value of your correlation coefficient and expressing it in percentage form to know how much of the dependent variable has been explained by the independent variable. Remember the number of variables you are studying also need to be considered.

Rainer Duesing (Universität Osnabrück)

If you collect data from the whole population, you do not need any inferential statistics! Inferential statistics is a method to estimate the population parameters from a sample and estimate the precision of your estimate. When the 24 samples are your population, then any parameter, mean, standard deciation, correlation is that of this specific population, there is no need to claculate any singnificance or anything like that. The evaluation of these parameters, e.g. correlation is  high vs. low, is up to you and your expertise. You will not find answers to this questions in inferential statistics.

Rainer Duesing (Universität Osnabrück)

Ok, than everything of inferential statistics applies to your sample, including the Fisher’s transformation, significance testing, power analysis etc., but also Spearman’s correction for attenuation, I hope this helps, otherwise just ask.

Saedah Siraj (Universiti Malaya)

If your study utilized  DDR as a design approach,  24 experts as your panel of FDM or ISM is ok.  But for the survey method you should add more sample.

Full discussion at:


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