Thesis Pearson Correlation

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When conducting a statistical test between two variables, it is a good idea to conduct a Pearson correlation coefficient value to determine just how strong that relationship is between those two variables.

In order to determine how strong the relationship is between two variables, a formula must be followed to produce what is referred to as the coefficient value.

You must find statistical significance in order to continue moving forward conducting the Pearson correlation coefficient.

The Pearson correlation coefficient, often referred to as the Pearson R test, is a statistical formula that measures the strength between variables and relationships.

Step one: Make a chart with your data for two variables, labeling the variables (x) and (y), and add three more columns labeled (xy), (x^2), and (y^2).

A simple data chart might look like this: Step five: Once you complete the formula above by plugging in all the correct values, the result is your coefficient value!

Therefore, you would have a negative correlation between the two variables, and the strength of the relationship would be weak.

You could confidently conclude there is a weak relationship and negative correlation between one's anxiety score and how many hours a week they report working.

You could confidently conclude there is a strong relationship and positive correlation between one's age and their income.

In other words, as people grow older, their income tends to increase as well.


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