Correlation Measurements with Microsoft Excel

Excel provides useful statistical functions for measuring the correlation between two variables. As a reminder, a benefit of using the correlation coefficient measures the relationship between two variables, as opposed to using covariance is that the unit of measurement is not important.

But caution: Remember that correlation does not demonstrate causality. It is easy to show that as the number of ice cream cones consumed increases during the year, so that the number of drownings. However, this does not mean that eating ice cream causes people to drown-more likely, these variables are both independently related to another variable, that of temperature. Correlation is symmetrical, so you get the same weight if they switch to a variable. Do not calculate the correlation coefficient if you manipulated one of the variables. Use linear regression instead.

CORREL

You're using the Correl function in Excel to determine whether two sets of data connection, and if so, how jako.Koeficijent correlation ranges from one indicating a perfect positive linear relationship, in order to -1, which indicates a perfect negative linear relationship. To calculate the correlation coefficient for the sample, Excel uses the sample covariance and standard deviation for each sample. To use the Correl function in Excel, just select the two sets of data used as an argument and use the following syntax:

= Correl (data set 1, data set 2)

For example, if you have a set of preliminary test results for a sample of employees in column
And a set of performance feedback results in column B, as shown in Figure 4-6, a
Want to find out whether they related and if so, how strongly, you can use Excel
find a correlation coefficient of the sample.

function returns a value of 0.87, which means that the sets are positively correlated (as the value
one goes up, the value of the other also increases), but the relationship is not perfect.

Pearson

Pearson's moment correlation coefficient product function, Pearson, using various
The equation for calculating the correlation coefficient. This formula does not require
computation of each deviation from the mean. However, the correlation coefficient ranged from
1, which indicates a perfect positive linear relationship, to -1, which indicates a perfect negative linear
odnos.Pearson function uses the following syntax:

= Pearson (data set 1, data set 2)

Using the Pearson function data is shown in Figure 4-6 to calculate the correlation coefficient returns the same value as the Correl function works.

RSQ

RSQ function calculates the square of the Pearson moment product correlation coefficient through data points in a data set. You can interpret the R-squared value as a proportion of the variance in y attributable to the variance in x.RSQ function uses the following syntax:
= RSQ (data set 1, data set 2)