The value of a diamond is determined by the four C's: carat weight, color, clarity, and cut.
Question:
The data represent a random sample of 40 unmounted, round-shaped diamonds. Use the data to answer the questions that follow:
(a) Determine the level of measurement for each variable.
(i) Carat weight
(ii) Color
(iii) Clarity
(iv) Cut
(v) Price
(vi) Shape
(b) Construct a correlation matrix. To do so, first convert the variables color, clarity, and cut to numeric values as follows:
Color: D = 1, E = 2, F = 3, G = 4, H = 5, I = 6, J = 7
Clarity: FL = 1, IF = 2, VVS1 = 3, VVS2 = 4, VS1 = 5,
VS2 = 6, SI1 = 7, SI2 = 8
Cut: Excellent = 1, Very Good = 2, Good = 3
If price is to be the response variable in our model, is there reason to be concerned about multicollinearity? Explain.
(c) Find the "best" model for predicting the price of a diamond.
(d) Draw residual plots, a boxplot of the residuals, and a normal probability plot of the residuals to assess the adequacy of the "best" model.
(e) For the "best" model, interpret each regression coefficient.
(f) Determine and interpret R2 and the adjusted R2.
(g) Predict the mean price of a round-shaped diamond with the following characteristics: 0.85 carat, E, VVS1, Excellent.
(h) Construct a 95% confidence interval for the mean price found in part (g).
(i) Predict the price of an individual round-shaped diamond with the following characteristics: 0.85 carat, E, VVS1 Excellent.
(j) Construct a 95% prediction interval for the price found in part (i).
(k) Explain why the predictions in parts (g) and (i) are the same, yet the intervals in parts (h) and (j) are different.
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Related Book For
Statistics Informed Decisions Using Data
ISBN: 9780134133539
5th Edition
Authors: Michael Sullivan III
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