What is a correlation analysis?
Correlation Analysis: Definition
Correlation analysis is a bivariate statistical method of measuring the strength of the linear relationship between two variables and calculating their relationship. Put simply, correlation analysis calculates the amount of change in one variable as the other changes. A high correlation indicates a strong relationship between the variables, while a low correlation means that the variables are weakly dependent on one another. With the help of the correlation analysis, relationships, patterns, significant connections and trends between two variables or data sets can be determined.
The correlation coefficient is the numerical value that indicates the type of correlation, that is, the statistical relationship between two variables. The value of the correlation coefficient (rs) varies between + 1 and - 1 in terms of the strength of the relationship between the variables. The closer the value of the correlation coefficient approaches 0, the weaker the relationship between the two variables. The direction of the relationship is indicated by the sign of the correlation coefficient; a + sign indicates a direct relationship and a - sign indicates an inverse relationship.
Carry out market research as a self-service
Examples of correlations
The correlation between two variables can be either a positive correlation, a negative correlation, or no correlation. Let's look at examples of each of these three types:
- Positive correlation: A positive correlation between two variables means that both variables are moving in the same direction. An increase in one variable leads to an increase in the other variable and vice versa. For example, if you spend more time on a treadmill, you burn more calories.
- Negative correlation: A negative correlation between two variables means that the variables are moving in opposite directions. An increase in one variable leads to a decrease in the other variable and vice versa. For example, as you increase the speed of a vehicle, the time it takes to get to your destination will decrease.
- Weak / zero correlation: There is no correlation if one variable has no influence on the other. For example, there is no correlation between the number of years a person has attended school and the number of letters in their first name.
Carry out correlation analysis without prior knowledge QuestionPro
With the help of the correlation analysis, it is relatively easy to determine the relationship between two variables. With the QuestionPro Analysis tools allow you to carry out correlation analyses without knowing the formula or manually evaluating data, for example in Excel.
Step 1: You have carried out a survey, customer survey or employee survey and now want to know whether two variables are interdependent. You call up the survey for which you want to carry out a correlation analysis and navigate to the ANALYTICS menu item and then select CORRELATION ANALYSIS under the ANALYSIS menu item.
Step 2: In the left pane, select the questions that you want to check for any correlation and click RECALCULATE CORRELATION COEFFICIENT.
Step 3: Interpret the results. The Threshold section helps you color-code the cells that indicate the strength of the relationship between the variables. In the case of a direct correlation, the threshold value is preset to 0,65 and has 3 colors. If the value of the correlation coefficient is below 0,80 to 0,65, the cell is colored light green, which indicates that the relationship is poor. If the value is between 0,80 and 0,90 the cell will be colored medium green, and if the value is above 0,90 the cell will be colored dark green, indicating a high correlation of the variables you selected earlier.
An Excel download with all color coding is supported for the correlation analysis. To do this, simply click on the XLS symbol.
And that was about it. Your correlation analysis is ready.