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Correlation Coefficient

Learn how to find the correlation coefficient. Determining the coefficient of correlation can help you understand, assess and comprehend a group of variables.

The correlation coefficient is a measure of how well two things are related. The correlation coefficient, abbreviated as r, indicates how well data in a scatter diagram follow a straight line. The closer the actual r value is to one, the better a linear equation can represent the data. There is next to no straight-line association in data sets with r values close to zero. The data collection is aligned if r = 1 or r = –1. 

The following are the three different types of correlation coefficients:

  • Pearson’s correlation coefficient
  • Spearman’s correlation
  • Kendall’s relationship

The formula for calculating the correlation coefficient

The following formula can be used to represent the sample correlation coefficient:

r=∑[(xix)(yiy)]√Σ(xix)2 ∗ Σ(yiy)2

(xi, yi)=a pair of data

=mean of xi

s(y) =deviation of the y coordinates’ second coordinates (i)

ȳ = mean of yi

IMPORTANT TAKEAWAYS 

  • The strength of the relationship between two variables is measured using the correlation coefficient.
  • In statistics, the correlation coefficient is commonly used. This metric assesses the direction and strength of a two-variable linear relationship.
  • The values are always between –1 (strongly negative relation) and +1 (strongly positive relation). A linear relation is weak or non-existent if the values are at or near zero.
  • Correlation coefficients of less than +0.8 or greater than –0.8 are deemed insignificant.

Steps for computing the correlation coefficient 

  1. Make a list of your data sets.

To begin the computation, generate a checklist of the variables you’ll be using. After you’ve created the data sets, plug these figures into your equation. These values are separated using the x and y variables.

 

  1. For each x variable, calculate the standardized value.

Use the following equation to determine the standardized value for each x(i) variable after you’ve selected your data sets.

(z(xi)) = (xi – x̅) / s(x)

  1. For each y variable, calculate the standardized value.

After you’ve determined the standardized value for each x(i), use the following equation to determine the standardized value for each y(i).

(z(yi))= (yi – ȳ) / s(y)

  1. Multiply and add to get the total.

Multiply the standardized values obtained in the previous steps. Use the formula shown below:

                                              (z(xi)) * (z(yi))

After you’ve multiplied the numbers, add them up to get the total.

  1. Calculate the correlation coefficient by dividing the total.

Use n to denote the total points in this information pair in the next step. Subtract n–1 from the result obtained in step 4.

Conclusion

The correlation coefficient is used to assess the strength of the relationship between two variables. The correlation coefficient is prefixed with the condition of the relationship between two variables. The correlation coefficient is represented as ‘r’. You can choose the highest coefficient of correlation by understanding the variables or information you are working with. 

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What is the correlation coefficient?

Ans.  In correlation analysis, the coefficient of correlation is a specific statistic that assesse...Read full

How are two variables related to one another?

Ans. The correlation of two variables is the statistical link between them. A positive correlation ...Read full

Is a correlation coefficient of 0.7 considered strong?

Ans.  A correlation is considered strong when the value of r is greater than 0.7. Any correlation ...Read full

What does a correlation coefficient of 0.9 signify?

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What is a high correlation coefficient?

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