Can you correlate different scales?

Can you correlate different scales?

1 Answer. Yes, it is perfectly valid to conduct a Pearson’s correlation between variables with different scales. The correlation coefficient is a standardized measure, so it is not influenced by scale.

Is Pearson correlation affected by scale?

A correlation value close to 0 indicates no association between the variables. Since the formula for calculating the correlation coefficient standardizes the variables, changes in scale or units of measurement will not affect its value.

What type of data is required for Pearson correlation test?

For a Pearson correlation, each variable should be continuous. If one or both of the variables are ordinal in measurement, then a Spearman correlation could be conducted instead.

Can you use Pearson correlation on Likert scale data?

Pearson correlation is used with variables measured on continious level {Interval or Ratio}. In case of likert scale, you need to compute the total score for the scale, after that do correlation with other continous variables.

Does correlation change after standardization?

No no need to standardize. Because by definition the correlation coefficient is independent of change of origin and scale. As such standardization will not alter the value of correlation.

Does standardization affect correlation?

Because by definition the correlation coefficient is independent of change of origin and scale. As such standardization will not alter the value of correlation.

What should the value of the Pearson correlation coefficient be?

The Pearson correlation coefficient, r, can take a range of values from +1 to -1. A value of 0 indicates that there is no association between the two variables. A value greater than 0 indicates a positive association; that is, as the value of one variable increases, so does the value of the other variable.

What is the definition of Pearson’s correlation in Stata?

Pearson’s Correlation using Stata. Introduction. The Pearson product-moment correlation coefficient, often shortened to Pearson correlation or Pearson’s correlation, is a measure of the strength and direction of association that exists between two continuous variables.

How to test a Pearson correlation between height and weight?

You can use a bivariate Pearson Correlation to test whether there is a statistically significant linear relationship between height and weight, and to determine the strength and direction of the association. In the sample data, we will use two variables: “Height” and “Weight.”

When to use Spearman’s correlation instead of Pearson’s?

If you are unsure whether your two variables are continuous (i.e., measured at the interval or ratio level), see our Types of Variable guide. Note: If either of your two variables were measured on an ordinal scale, you need to use Spearman’s correlation instead of Pearson’s correlation.