PSY 0371 Week 1 Assignment 6

PSY 0371  Week 1 Assignment 6 | San Francisco State University | Assignment Help

Homework 6 Part 1

Continue to record the following information every day (up through December 1, 2020):

1.     the number of hours of sleep you got (s = sleep)

2.     the number of cups of caffeine drinks you had (c = caffeinated drinks)

3.     the number of cups of non-caffeinated drinks you had (nc = non-caffeinated drinks)

4.     the number of hours you spent looking at a phone, computer screen, TV, etc. (d = hours looking at a device)

(NOTE: round hours to the nearest half hour ; count each drink - however big or small - as one drink.  And remember to report the date on which you recorded your data.)

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Homework 6 has two parts.  This is Part 1, which is due on Friday, November 13.  Part 2 will be posted by Monday, November 9; Part 2 will be due on Monday, November 16.

(A)  First, submit all of the data you have collected this semester up through Friday, November 6 to your GTA.  Please submit the data to your GTA using a spreadsheet program, like Microsoft Excel. (If you do not have access to Excel, please contact your GTA and work out how best to get the data to your GTA.)  Your data should have 5 columns.  The first column will be the date, the second column will be the number of hours of sleep you got that night, the third column will be the number of cups of caffeine you had, the fourth column will be the number of non-caffeinated drinks you had, and the fifth column will be the number of hours of hours you spent looking at a phone, computer screen, TV, etc.

(B) Calculate the Pearson product-moment correlation coefficient, r, between number of cups of caffeine you had and the number of non-caffeinated drinks you had for the 5 weekdays last week: Monday, October 26 through Friday, October 30.  To do this, follow the instructions for Homework 5, but calculate the correlation for caffeinated and non-caffeinated drinks. Be sure to report answers corresponding to each part of Homework 5, but also show all of your work.

(C) Draw a scatterplot for these data (again, following the instructions from Homework 5).

You will need the results of your work on Part 1 in order to complete Part 2.  You can get started on Part 1 above any time, and start work on Part 2 when it is available.

 Homework 6 Part 2

I was going to have you do Part 2 of Homework 6 using the results you got from Part 1 of Homework 6.  But because not everyone got a value for the Pearson product-moment correlation coefficient that was in the possible range (i.e., some people got r < -1 or r > +1, which cannot be the case), use the following set-up for Part 2 of Homework 6:

For the five days from October 26-30, 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:

From these data, one can calculate the mean and standard deviation for X (i.e., # of caffeinated drinks) and the mean and standard deviation for Y (i.e., # of non-caffeinated drinks) to be:

To calculate the Pearson product-moment correlation coefficient (r) between X and Y, one first converts the scores in X to their corresponding z-scores (by dividing the mean deviation of X by the standard deviation of X) and the scores in Y to their corresponding z-scores (by dividing the mean deviation of Y by the standard deviation of Y).  Then multiply z_X and z_Y for each of the five days to get the five products of z-scores. 

r is just the mean of these five products of z-scores:

r = [ (-1.28) + (-.86) + 0 + (-2.58) + (-.22) ] / 5 = -4.94/5 = -0.99

Answer the following questions using the correlation reading:

1. Is this a positive or a negative correlation?

2. Is this a strong or a weak correlation?

3. Draw a scatterplot for these data.

4. Calculate the coefficient of determination.

Answer the following questions using the regression reading:

5. Sam had 3 caffeinated drinks on October 31.  Use linear regression to predict the number non-caffeinated drinks he had on October 31.

6. Calculate the standard error of estimate for your prediction in (5) above.

7. Sam had 3 non-caffeinated drinks on November 1.  Use linear regression to predict the number of caffeinated drinks he had on November 1.

8. Calculate the standard error of estimate for your prediction in (7) above.

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Hint:

1. Find "coefficient of determination" at the last part of the reading 3.1 on the site of PSY 371-11.
2. Prediction and standard error of estimate were introduced on the reading 3.2