Actually, both parts 1.a. AND 1.b. should treat Sheerluck's data as if they were the SAME measurements on two samples of 5 DIFFERENT constables, and it is part 1.c. that should treat the data the way I intended when I wrote t he problem, that they be two DIFFERENT measurements on the SAME set of constables. Note from teacher!
Brightly blarney but blissfully blas´e bloodhound Sheerluck Hopeless has trained herself to recognize at a glance suspect heights and weights. From experience she has found that her estimation errors tend to follow approximately Normal distributions. Hopeless tests her estimation abilities on five London constables: her estimation errors, in cm and kg, are given in the table below:
Hopeless Errors
Heights (cm) -0.6 -0.2 0.2 0.5 0.6
Weights (kg) -1.2 -0.7 -0.1 0.1 0.9
“My compliments, Hopeless!” Dr. Witless puzzled, “To find the probability a thing does NOT happen, how did you describe it?”
“Complementary, my dear Witless,” Hopeless rubbed her eyes, bowed her head, and exhaled an uncomplimentary sigh, “Complementary!”
b. Test that there IS a difference between Sheerluck’s mean estimation errors for
suspect heights and weights against the hypothesis of NO difference.
c. Compare Sheerluck’s estimation errors for heights against weights:
i. Draw a simple plots of weight errors (y) against height errors (x). (5)
ii. Find the correlation coefficient between Sheerluck’s two types of errors. (5)
iii. Find the regression line for weight errors as a function of height errors. (10)
iv. Use the coefficient of variation to interpret how well this linear model explains
the relationship between Sheerluck’s height and weight estimation errors.
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