Question about correlation coefficient

In summary, Luca has 32 responses from a survey and 63 instances of company performance data over a 5 year period. They are trying to correlate employee attitudes towards company performance, but it is important to consider the context and potential limitations of using a linear correlation in this situation.
  • #1
pamparana
128
0
Hello everyone,

I have a question (perhaps a very noob one as well!) regarding correlation between variables where the number of observations are different between the two sets.

So, I have some 32 responses generated from a survey which aim to measure certain variable and I want to correlate them against some company performance indicators. Now these performance indicators are available per month basis for like 63 months.

Now, I have 32 instances of a variable against 63 instances of another. Is it possible to do a simple correlation within these sets where the number of instances are different...

Thanks,
Luca
 
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  • #2
What, precisely, would you be correlating, exactly? What is the relationship between the two variables that would allow a correlation to make sense? How do you know which variables in one measure are associated with which variables in another?

Correlation is, fundamentally, normalized covariance, which is a characteristic of joint distributions of random variables. If you have two uneven sets of completely unrelated and unpaired data, then the notion of correlation makes no sense.
 
  • #3
Are the 32 responses spread across the same 63 month period?
 
  • #4
Hello,

Thanks for the replies. The 32 responses are from employees that have been employed over that 5 year period.

What I am trying to correlate is employee attitudes towards company performance over that time.

Thanks,
Luca
 
  • #5
You should be aware that correlation in its most common form between two variables, only makes sense when the relationship is linear (since this is is what it is trying to determine).

You need to take a look at your data and decide whether you can discern any relationship at all, and if necessary transform your data to try and get a linear-looking relationship.

The most important thing however is try put context into your data: if you can quantify the characteristics of the behaviour with a simple function that makes sense non-mathematically (i.e. you can explain what it means in plain english without using mathematics and with a reference to something specific) then this is what you should be doing.

If you are just trying to produce metrics without having a clue what's going on, you'll be setting yourself up to make a potentially bad decision.
 
  • #6
pamparana said:
Hello,

Thanks for the replies. The 32 responses are from employees that have been employed over that 5 year period.

What I am trying to correlate is employee attitudes towards company performance over that time.

Thanks,
Luca

So you have performance data on a per month basis for 63 months, and survey data every month as well? If you only have survey data at one time point, I'm not sure what you would correlate, exactly.
 

1. What is a correlation coefficient?

A correlation coefficient is a statistical measure that determines the strength and direction of the relationship between two variables. It ranges from -1 to 1, with higher values indicating a stronger correlation.

2. How is a correlation coefficient calculated?

A correlation coefficient is calculated by dividing the covariance of the two variables by the product of their standard deviations.

3. What does a correlation coefficient of 0 mean?

A correlation coefficient of 0 indicates that there is no linear relationship between the two variables. However, there may still be a non-linear relationship present.

4. How do you interpret a negative correlation coefficient?

A negative correlation coefficient indicates an inverse relationship between the two variables, meaning that as one variable increases, the other decreases. The closer the coefficient is to -1, the stronger the inverse relationship.

5. Can a correlation coefficient determine causality?

No, a correlation coefficient cannot determine causality. It only measures the strength and direction of the relationship between two variables, but does not prove that one variable causes the other.

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