6. Disk drives 2014 again Recall the data on disk drives we saw in Chapter 6, Exercise 4. Suppose we want to predict Price from Capacity. Number of Sales People Working Sales (in $1000) 2 10 3 11 7 13 9 14 10 18 10 20 12 20 15 22 16 22 20 26 x = 10.4 y = 17.6 SD(x) = 5.64 SD(y) = 5.34 r = 0.965

a) Find the slope estimate, b1.

b) What does it mean, in this context?

c) Find the intercept, b0.

d) What does it mean, in this context? Is it meaningful?

e) Write down the equation that predicts Sales from Number of Sales People Working.

f) If 18 people are working, what Sales do you predict? g) If sales are actually $25 000, what is the value of the residual? h) Have we overestimated or underestimated the sales? Capacity (in TB) Price (in $) 0.50 59.99 1.0 79.99 2.0 111.97 3.0 109.99 4.0 149.99 6.0 423.34 8.0 596.11 12.0 1079.99 32.0 4461.00 x = 7.6111 y = 785.819 SD(x) = 9.855 SD(y) = 1418.67 r = 0.9876

a) Find the slope estimate, b1.

b) What does it mean, in this context?

c) Find the intercept, b0.

d) What does it mean, in this context? Is it meaningful?

e) Write down the equation that predicts Price from Capacity.

f) What would you predict for the price of a 20 TB drive? g) A 20 TB drive on Amazon.com was listed at $2017.86. According to the model, does this seem like a good buy? How much would you save compared to what you expected to pay? h) Does the model overestimate or underestimate the price? i) The correlation is very high. Does this mean that the model is accurate? Explain. (Hint: Revisit the scatterplot from Chapter 6, Exercise 4.)