Academic Integrity: tutoring, explanations, and feedback — we don’t complete graded work or submit on a student’s behalf.

Apply the principles to create a well-designed scatterplot of X Vs. Y 1: Use jit

ID: 3275387 • Letter: A

Question

Apply the principles to create a well-designed scatterplot of X Vs. Y

1: Use jittering if appropriate.

2: If jittering is appropriate for this scatterplot explain why.

3: Use a dark blue, solid disk of appropriate size as the plotting symbol.

4: Use the Minitab lowess smoothing function to add an appropriately smoothed curve to the scatterplot.

5: Explain why smoothing is frequently used prior to conducting a regression analysis.

6: Next add a simple linear regression line to the scatterplot.

7: Paste the regression equation from part (b) below into your graph. Paste your graph (approximately 3”x 4”) into a word file for submission.

Child Midparent
61.7 70.5
61.7 68.5
61.7 65.5
61.7 64.5
61.7 64.0
62.2 67.5
62.2 67.5
62.2 67.5
62.2 66.5
62.2 66.5
62.2 66.5
62.2 64.5
63.2 70.5
63.2 69.5
63.2 68.5
63.2 68.5
63.2 68.5
63.2 68.5
63.2 68.5
63.2 68.5
63.2 68.5
63.2 67.5
63.2 67.5
63.2 67.5
63.2 67.5
63.2 67.5
63.2 66.5
63.2 66.5
63.2 66.5
63.2 65.5
63.2 65.5
63.2 65.5
63.2 65.5
63.2 65.5
63.2 65.5
63.2 65.5
63.2 65.5
63.2 65.5
63.2 64.5
63.2 64.5
63.2 64.5
63.2 64.5
63.2 64.0
63.2 64.0
64.2 69.5
64.2 69.5
64.2 69.5
64.2 69.5
64.2 69.5
64.2 69.5
64.2 69.5
64.2 69.5
64.2 69.5
64.2 69.5
64.2 69.5
64.2 69.5
64.2 69.5
64.2 69.5
64.2 69.5
64.2 69.5
64.2 68.5
64.2 68.5
64.2 68.5
64.2 68.5
64.2 68.5
64.2 68.5
64.2 68.5
64.2 68.5
64.2 68.5
64.2 68.5
64.2 68.5
64.2 67.5
64.2 67.5
64.2 67.5
64.2 67.5
64.2 67.5
64.2 67.5
64.2 67.5
64.2 67.5
64.2 67.5
64.2 67.5
64.2 67.5
64.2 67.5
64.2 67.5
64.2 67.5
64.2 66.5
64.2 66.5
64.2 66.5
64.2 66.5
64.2 66.5
64.2 65.5
64.2 65.5
64.2 65.5
64.2 65.5
64.2 65.5
64.2 64.5
64.2 64.5
64.2 64.5
64.2 64.5
64.2 64.0
64.2 64.0
64.2 64.0
64.2 64.0
65.2 71.5
65.2 70.5
65.2 69.5
65.2 69.5
65.2 69.5
65.2 69.5
65.2 68.5
65.2 68.5
65.2 68.5
65.2 68.5
65.2 68.5
65.2 68.5
65.2 68.5
65.2 68.5
65.2 68.5
65.2 68.5
65.2 68.5
65.2 68.5
65.2 68.5
65.2 68.5
65.2 68.5
65.2 68.5
65.2 67.5
65.2 67.5
65.2 67.5
65.2 67.5
65.2 67.5
65.2 67.5
65.2 67.5
65.2 67.5
65.2 67.5
65.2 67.5
65.2 67.5
65.2 67.5
65.2 67.5
65.2 67.5
65.2 67.5
65.2 66.5
65.2 66.5
65.2 65.5
65.2 65.5
65.2 65.5
65.2 65.5
65.2 65.5
65.2 65.5
65.2 65.5
65.2 64.5
65.2 64.0
66.2 71.5
66.2 71.5
66.2 71.5
66.2 70.5
66.2 69.5
66.2 69.5
66.2 69.5
66.2 69.5
66.2 69.5
66.2 69.5
66.2 69.5
66.2 69.5
66.2 69.5
66.2 69.5
66.2 69.5
66.2 69.5
66.2 69.5
66.2 69.5
66.2 69.5
66.2 69.5
66.2 69.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 68.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 67.5
66.2 66.5
66.2 66.5
66.2 66.5
66.2 66.5
66.2 66.5
66.2 66.5
66.2 66.5
66.2 66.5
66.2 66.5
66.2 66.5
66.2 66.5
66.2 66.5
66.2 66.5
66.2 66.5
66.2 66.5
66.2 66.5
66.2 66.5
66.2 65.5
66.2 65.5
66.2 65.5
66.2 65.5
66.2 65.5
66.2 65.5
66.2 65.5
66.2 65.5
66.2 65.5
66.2 65.5
66.2 65.5
66.2 64.5
66.2 64.5
66.2 64.5
66.2 64.5
66.2 64.5
66.2 64.0
66.2 64.0
67.2 71.5
67.2 71.5
67.2 71.5
67.2 71.5
67.2 70.5
67.2 70.5
67.2 70.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 69.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 68.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 67.5
67.2 66.5
67.2 66.5
67.2 66.5
67.2 66.5
67.2 66.5
67.2 66.5
67.2 66.5
67.2 66.5
67.2 66.5
67.2 66.5
67.2 66.5
67.2 66.5
67.2 66.5
67.2 66.5
67.2 66.5
67.2 66.5
67.2 66.5
67.2 65.5
67.2 65.5
67.2 65.5
67.2 65.5
67.2 65.5
67.2 65.5
67.2 65.5
67.2 65.5
67.2 65.5
67.2 65.5
67.2 65.5
67.2 64.5
67.2 64.5
67.2 64.5
67.2 64.5
67.2 64.5
67.2 64.0
67.2 64.0
68.2 72.5
68.2 71.5
68.2 71.5
68.2 71.5
68.2 70.5
68.2 70.5
68.2 70.5
68.2 70.5
68.2 70.5
68.2 70.5
68.2 70.5
68.2 70.5
68.2 70.5
68.2 70.5
68.2 70.5
68.2 70.5
68.2 69.5
68.2 69.5
68.2 69.5
68.2 69.5
68.2 69.5
68.2 69.5
68.2 69.5
68.2 69.5
68.2 69.5
68.2 69.5
68.2 69.5
68.2 69.5
68.2 69.5
68.2 69.5
68.2 69.5
68.2 69.5
68.2 69.5
68.2 69.5
68.2 69.5
68.2 69.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 68.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 67.5
68.2 66.5
68.2 66.5
68.2 66.5
68.2 66.5
68.2 66.5
68.2 66.5
68.2 66.5
68.2 66.5
68.2 66.5
68.2 66.5
68.2 66.5
68.2 66.5
68.2 66.5
68.2 66.5
68.2 65.5
68.2 65.5
68.2 65.5
68.2 65.5
68.2 65.5
68.2 65.5
68.2 65.5
68.2 64.0
69.2 72.5
69.2 72.5
69.2 71.5
69.2 71.5
69.2 71.5
69.2 71.5
69.2 71.5
69.2 70.5
69.2 70.5
69.2 70.5
69.2 70.5
69.2 70.5
69.2 70.5
69.2 70.5
69.2 70.5
69.2 70.5
69.2 70.5
69.2 70.5
69.2 70.5
69.2 70.5
69.2 70.5
69.2 70.5
69.2 70.5
69.2 70.5
69.2 70.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 69.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 68.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 67.5
69.2 66.5
69.2 66.5
69.2 66.5
69.2 66.5
69.2 66.5
69.2 66.5
69.2 66.5
69.2 66.5
69.2 66.5
69.2 66.5
69.2 66.5
69.2 66.5
69.2 66.5
69.2 65.5
69.2 65.5
69.2 65.5
69.2 65.5
69.2 65.5
69.2 65.5
69.2 65.5
69.2 64.5
69.2 64.5
69.2 64.0
70.2 72.5
70.2 71.5
70.2 71.5
70.2 71.5
70.2 71.5
70.2 71.5
70.2 71.5
70.2 71.5
70.2 71.5
70.2 71.5
70.2 71.5
70.2 70.5
70.2 70.5
70.2 70.5
70.2 70.5
70.2 70.5
70.2 70.5
70.2 70.5
70.2 70.5
70.2 70.5
70.2 70.5
70.2 70.5
70.2 70.5
70.2 70.5
70.2 70.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 69.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 68.5
70.2 67.5
70.2 67.5
70.2 67.5
70.2 67.5
70.2 67.5
70.2 67.5
70.2 67.5
70.2 67.5
70.2 67.5
70.2 67.5
70.2 67.5
70.2 67.5
70.2 67.5
70.2 67.5
70.2 67.5
70.2 67.5
70.2 67.5
70.2 67.5
70.2 67.5
70.2 66.5
70.2 66.5
70.2 66.5
70.2 66.5
70.2 65.5
70.2 65.5
70.2 65.5
70.2 65.5
70.2 65.5
71.2 72.5
71.2 72.5
71.2 71.5
71.2 71.5
71.2 71.5
71.2 71.5
71.2 70.5
71.2 70.5
71.2 70.5
71.2 70.5
71.2 70.5
71.2 70.5
71.2 70.5
71.2 69.5
71.2 69.5
71.2 69.5
71.2 69.5
71.2 69.5
71.2 69.5
71.2 69.5
71.2 69.5
71.2 69.5
71.2 69.5
71.2 69.5
71.2 69.5
71.2 69.5
71.2 69.5
71.2 69.5
71.2 69.5
71.2 69.5
71.2 69.5
71.2 69.5
71.2 69.5
71.2 68.5
71.2 68.5
71.2 68.5
71.2 68.5
71.2 68.5
71.2 68.5
71.2 68.5
71.2 68.5
71.2 68.5
71.2 68.5
71.2 68.5
71.2 68.5
71.2 68.5
71.2 68.5
71.2 68.5
71.2 68.5
71.2 68.5
71.2 68.5
71.2 67.5
71.2 67.5
71.2 67.5
71.2 67.5
71.2 67.5
71.2 67.5
71.2 67.5
71.2 67.5
71.2 67.5
71.2 67.5
71.2 67.5
71.2 65.5
71.2 65.5
72.2 73.0
72.2 72.5
72.2 72.5
72.2 72.5
72.2 72.5
72.2 72.5
72.2 72.5
72.2 72.5
72.2 71.5
72.2 71.5
72.2 71.5
72.2 71.5
72.2 71.5
72.2 71.5
72.2 71.5
72.2 71.5
72.2 71.5
72.2 70.5
72.2 70.5
72.2 70.5
72.2 70.5
72.2 69.5
72.2 69.5
72.2 69.5
72.2 69.5
72.2 69.5
72.2 69.5
72.2 69.5
72.2 69.5
72.2 69.5
72.2 69.5
72.2 69.5
72.2 68.5
72.2 68.5
72.2 68.5
72.2 68.5
72.2 67.5
72.2 67.5
72.2 67.5
72.2 67.5
72.2 65.5
73.2 73.0
73.2 73.0
73.2 73.0
73.2 72.5
73.2 72.5
73.2 71.5
73.2 71.5
73.2 70.5
73.2 70.5
73.2 70.5
73.2 69.5
73.2 69.5
73.2 69.5
73.2 69.5
73.2 68.5
73.2 68.5
73.2 68.5
73.7 72.5
73.7 72.5
73.7 72.5
73.7 72.5
73.7 71.5
73.7 71.5
73.7 70.5
73.7 70.5
73.7 70.5
73.7 69.5
73.7 69.5
73.7 69.5
73.7 69.5
73.7 69.5
61.7 70.5

Explanation / Answer

1.

x=read.csv("Book23.csv")
Ch=x[,1]
MP=x[,2]
par(mfrow=c(2,2))
plot(Ch~MP, pch=15)
plot(Ch~jitter(MP), pch=15)
plot(jitter(Ch)~MP, pch=15)
plot(jitter(Ch)~jitter(MP), pch=15)

2 We have discrete data that is almost continuous becuase sometimes symbols are plotted on top of one another so much that the relationship is obscured. THus, variables might be approximately linear with other variables.

3.

4,5 Minitab is not there

7, 8