For the five days from April 19-23, Sam counted the number of cups of caffeinated drinks he consumed (X) and the number of non-caffeinated drinks he consumed (Y).  The following were the raw data for X and Y: Date X = # caffeinated drinks Y = # non-caffeinated drinks April 19 3 5 April 20 4 5 April 21 6 3 April 22 10 0 April 23 7 2 The mean and standard deviation for X (i.e., # of caffeinated drinks Sam drank) and the mean and standard deviation for Y (i.e., # of non-caffeinated drinks Sam drank) are

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.4: Distributions Of Data
Problem 19PFA
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For the five days from April 19-23, Sam counted the number of cups of caffeinated drinks he consumed (X) and the number of non-caffeinated drinks he consumed (Y).  The following were the raw data for X and Y:

Date X = # caffeinated drinks Y = # non-caffeinated drinks
April 19 3 5
April 20 4 5
April 21 6 3
April 22 10 0
April 23 7 2
The mean and standard deviation for X (i.e., # of caffeinated drinks Sam drank) and the mean and standard deviation for Y (i.e., # of non-caffeinated drinks Sam drank) are:
meanX = 6       meanY = 3.6
stdDevX = 2.45       stdDevY = 1.9
 
Answer the following questions using the correlation reading:
1. Calculate the Pearson product-moment correlation coefficient, r, between X and Y for Sam.
2. Is this a positive or a negative correlation?
3. Is this a strong or a weak correlation?
4. Draw a scatterplot for these data.
5. Calculate the coefficient of determination.
 
Answer the following questions using the regression reading:
6. Sam had 3 caffeinated drinks on April 24.  Use linear regression to predict the number non-caffeinated drinks he had on April 24.
7. Calculate the standard error of estimate for your prediction in (6) above.
8. Sam had 3 non-caffeinated drinks on April 25.  Use linear regression to predict the number of caffeinated drinks he had on April 25.
9. Calculate the standard error of estimate for your prediction in (8) above.

 

 

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