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Carl
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After a sample size of 400+ I was able to get a Pearson's coefficient of .25. How am I supposed to break this down into a probability or a percentage. Rather, how can I explain my findings in laymen terms?

I should give some more information. We have two different tests. One of these tests has 1 question, How satisfied are you? It is scored between a 1-4, with 4 being the most satisfied and 1 being the lowest. The other test has 18 questions. These were an internal review. The review consisted of such questions (did the customer service rep use the customer's name, did the customer service rep give the correct technical answer, did the rep teach the customer how to fix the problem themselves if applicable).

The first test is asked to the customer, the second test with its 18 different questions is filled out by the supervisor. They either pass (-1), Not Applicable or Neither Pass/Fail (0), or Fail (1).

Our goal is to find which variables in the second test best predict scores in the first test. We want to do this to find the problem areas that we can fix internally in order to better serve our customer and give them the best experience possible (More 3's and 4's on the first test).

After a sample size of 400+ I was able to get a Pearson's coefficient of .25. How am I supposed to break this down into a probability or a percentage. Rather, how can I explain my findings in laymen terms?

After a sample size of 400+ I was able to get a Pearson's coefficient of .25. How am I supposed to break this down into a probability or a percentage. Rather, how can I explain my findings in laymen terms?

I should give some more information. We have two different tests. One of these tests has 1 question, How satisfied are you? It is scored between a 1-4, with 4 being the most satisfied and 1 being the lowest. The other test has 18 questions. These were an internal review. The review consisted of such questions (did the customer service rep use the customer's name, did the customer service rep give the correct technical answer, did the rep teach the customer how to fix the problem themselves if applicable).

The first test is asked to the customer, the second test with its 18 different questions is filled out by the supervisor. They either pass (-1), Not Applicable or Neither Pass/Fail (0), or Fail (1).

Our goal is to find which variables in the second test best predict scores in the first test. We want to do this to find the problem areas that we can fix internally in order to better serve our customer and give them the best experience possible (More 3's and 4's on the first test).

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gung - Reinstate Monica
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Using Pearson's Correlation Coefficientcorrelation coefficient for Probabilityprobability

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Carl
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Using Pearson's Correlation Coefficient for Probability

After a sample size of 400+ I was able to get a Pearson's coefficient of .25. How am I supposed to break this down into a probability or a percentage. Rather, how can I explain my findings in laymen terms?