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Scores are not variables, there are only two variables not 10. Thanks.
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edit approved Jun 17, 2017 at 15:54
Heteroskedastic Jim
edit approved Jun 17, 2017 at 15:54
Heteroskedastic Jim
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I have made some research and I acquired the following data:

  • 40 "packs" of data
  • each "pack" contains 10 variablesscores of variable A and 10 variablesscores of variable B
  • A is always 1,2,3,4,5,6,7,8,9,10
  • B is a measurement result and scores in 0-100%

My thesis is: the higher A, the lower B.

Now, having all this info, I have used Shapiro-Wilk test on every "pack" to deremine normality and p value was always > 0.05. Based on the data I have and the results of SW test, I concluded that Pearson Correlation Coefficient is the right choice here. I calculated the correlation and that's where I am at this moment.

Question 1: Can I calculate the average of B for every A (i.e. avarege of B where A = 1 from all "packs", repeat for all rows 1-10) and then use Pearson to calculate the correlation of the averages? Is this valid approach?

Question 2: Are there any other statistics that may be important for my thesis and this set of data apart from correlations?

Question 3: Should I draw a conclusion from all the individual results? Or from the average? Or maybe something else?

I am not a statistician in my daily work, so I would be very grateful for any help. Thank you.

I have made some research and I acquired the following data:

  • 40 "packs" of data
  • each "pack" contains 10 variables of A and 10 variables of B
  • A is always 1,2,3,4,5,6,7,8,9,10
  • B is a measurement result and scores in 0-100%

My thesis is: the higher A, the lower B.

Now, having all this info, I have used Shapiro-Wilk test on every "pack" to deremine normality and p value was always > 0.05. Based on the data I have and the results of SW test, I concluded that Pearson Correlation Coefficient is the right choice here. I calculated the correlation and that's where I am at this moment.

Question 1: Can I calculate the average of B for every A (i.e. avarege of B where A = 1 from all "packs", repeat for all rows 1-10) and then use Pearson to calculate the correlation of the averages? Is this valid approach?

Question 2: Are there any other statistics that may be important for my thesis and this set of data apart from correlations?

Question 3: Should I draw a conclusion from all the individual results? Or from the average? Or maybe something else?

I am not a statistician in my daily work, so I would be very grateful for any help. Thank you.

I have made some research and I acquired the following data:

  • 40 "packs" of data
  • each "pack" contains 10 scores of variable A and 10 scores of variable B
  • A is always 1,2,3,4,5,6,7,8,9,10
  • B is a measurement result and scores in 0-100%

My thesis is: the higher A, the lower B.

Now, having all this info, I have used Shapiro-Wilk test on every "pack" to deremine normality and p value was always > 0.05. Based on the data I have and the results of SW test, I concluded that Pearson Correlation Coefficient is the right choice here. I calculated the correlation and that's where I am at this moment.

Question 1: Can I calculate the average of B for every A (i.e. avarege of B where A = 1 from all "packs", repeat for all rows 1-10) and then use Pearson to calculate the correlation of the averages? Is this valid approach?

Question 2: Are there any other statistics that may be important for my thesis and this set of data apart from correlations?

Question 3: Should I draw a conclusion from all the individual results? Or from the average? Or maybe something else?

I am not a statistician in my daily work, so I would be very grateful for any help. Thank you.

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Sikor
Sikor
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Should I draw the conclusions from average or individual data? Is this approach using Pearson CC correct?

I have made some research and I acquired the following data:

  • 40 "packs" of data
  • each "pack" contains 10 variables of A and 10 variables of B
  • A is always 1,2,3,4,5,6,7,8,9,10
  • B is a measurement result and scores in 0-100%

My thesis is: the higher A, the lower B.

Now, having all this info, I have used Shapiro-Wilk test on every "pack" to deremine normality and p value was always > 0.05. Based on the data I have and the results of SW test, I concluded that Pearson Correlation Coefficient is the right choice here. I calculated the correlation and that's where I am at this moment.

Question 1: Can I calculate the average of B for every A (i.e. avarege of B where A = 1 from all "packs", repeat for all rows 1-10) and then use Pearson to calculate the correlation of the averages? Is this valid approach?

Question 2: Are there any other statistics that may be important for my thesis and this set of data apart from correlations?

Question 3: Should I draw a conclusion from all the individual results? Or from the average? Or maybe something else?

I am not a statistician in my daily work, so I would be very grateful for any help. Thank you.