Correlation coefficient example Correlation coefficient

Correlation coefficient example

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Correlation coefficient is used to derive a relationship between two or more variables in a given dataset. Apart from that, correlation coefficient can also defines how strong the relationship is.

In this article we will see an example of correlation coefficient and how it can be calculated: 

Correlation coefficient formula:

Correlation coefficient example Correlation coefficient

Where, 

  • n=Quantity of information
  • Σx=Total of all values for first variable
  • Σy=Total of all values for second variable
  • Σxy=Sum of product of first and second value
  • Σx2=Sum of squares of the first value
  • Σy2=Sum of squares of the second value

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Steps to perform correlation coefficient:

Step 1: Make a table of the given data. In our case, given below is a table that shows students’ marks before (x) and marks after (y) special training in the subject English.

Correlation coefficient example Correlation coefficient

Step 2: Now add three columns for xy, x2, and y2.

Correlation coefficient example Correlation coefficient

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  • Step 3: Now add all the columns to find each of their SUM (Σ)
Correlation coefficient example Correlation coefficient

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  • Step 4: Next, use the correlation coefficient formula and substitute the values in the formula from the table.
Correlation coefficient example Correlation coefficient
  • n = 6
  • Σx = 247
  • Σy = 474
  • Σxy = 20522
  • Σx2 = 11409
  • Σy2 = 38648

Substituting in the formula;

r = 6(20522) – (247) (474) / √ [6(11409) – (247)2] [6(38648) – (474)2]

r = 123132 – 117078 / √ [68454 – 61009] [231888 – 224676] 

r = 6054 / √ (7445) (7212) 

r = 6054 / √ 53693340

r = 6054 / 7327.57

r = 0.826

  • Step 5: Analyse the results

In our example, we got a correlation coefficient of 0.826. Which is 82%. 

  • +1 indicates a strong positive relationship.
  • -1 indicates a strong negative relationship.
  • A result of zero indicates no relationship at all. 

Since our coefficient is more than 0 and slightly less than +1 that is, we can say that the variables have a positive correlation

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