Question: Failure times of silicon wafer microchips. Refer to the National Semiconductor study of manufactured silicon wafer integrated circuit chips, Exercise 12.63 (p. 749). Recall that the failure times of the microchips (in hours) was determined at different solder temperatures (degrees Celsius). The data are repeated in the table below.

  1. Fit the straight-line modelEy=β0+β1xto the data, where y = failure time and x = solder temperature.

  2. Compute the residual for a microchip manufactured at a temperature of 149°C.

  3. Plot the residuals against solder temperature (x). Do you detect a trend?

  4. In Exercise 12.63c, you determined that failure time (y) and solder temperature (x) were curvilinearly related. Does the residual plot, part c, support this conclusion?

Short Answer

Expert verified
  1. From the excel output below, the straight-line model for y on x can be written asEy=30855.91-191.567x.

  2. Residual value; ε = (2312.427 - 1,100) = 1212.427

  3. From the excel output, the residual plot denotes a curvilinear relationship amongst the residuals against solder temperature (x).

  4. From the graph, it can be concluded that there exists a curvilinear relationship between failure time (y) and solder temperature (x) as the residual plot indicates a curvilinear relationship

Step by step solution

01

Straight-line model

From the excel output below, the straight-line model for y on x can be written as Ey= 30855.91 - 191.567x.


02

Prediction value

The residual for a microchip manufactured at a temperature of 149°C can be computed using

ε = y^-y For x = 149, y = 1, 100 and y^= 30855.91 - 191.567149y^= 2312.427

Therefore, ε = 2312.427-1,100= 1212.427

03

Residual plot

From the excel output, the residual plot denotes a curvilinear relationship amongst the residuals against solder temperature (x).

04

Residual plot interpretation

From the graph, it can be concluded that there exists a curvilinear relationship between failure time (y) and solder temperature (x) as the residual plot indicates a curvilinear relationship.

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Most popular questions from this chapter

Ascorbic acid reduces goat stress. Refer to the Animal Science Journal (May, 2014) study on the use of ascorbic acid (AA) to reduce stress in goats during transportation from farm to market, Exercise 9.12 (p. 529). Recall that 24 healthy goats were randomly divided into four groups (A, B, C, and D) of six animals each. Goats in group A were administered a dosage of AA 30 minutes prior to transportation; goats in group B were administered a dosage of AA 30 minutes following transportation; group C goats were not given any AA prior to or following transportation; and, goats in group D were not given any AA and were not transported. Weight was measured before and after transportation and the weight loss (in kilograms) determined for each goat.

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Assertiveness and leadership. Management professors at Columbia University examined the relationship between assertiveness and leadership (Journal of Personality and Social Psychology, February 2007). The sample represented 388 people enrolled in a full-time MBA program. Based on answers to a questionnaire, the researchers measured two variables for each subject: assertiveness score (x) and leadership ability score (y). A quadratic regression model was fit to the data, with the following results:

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Question: Chemical plant contamination. Refer to Exercise 12.18 (p. 725) and the U.S. Army Corps of Engineers study. You fit the first-order model,E(Y)=β0+β1x1+β2x2+β3x3 , to the data, where y = DDT level (parts per million),X1= number of miles upstream,X2= length (centimeters), andX3= weight (grams). Use the Excel/XLSTAT printout below to predict, with 90% confidence, the DDT level of a fish caught 300 miles upstream with a length of 40 centimeters and a weight of 1,000 grams. Interpret the result.

Question: Manipulating rates of return with stock splits. Some firms have been accused of using stock splits to manipulate their stock prices before being acquired by another firm. An article in Financial Management (Winter 2008) investigated the impact of stock splits on long-run stock performance for acquiring firms. A simplified version of the model fit by the researchers follows:

E(y)=β0+β1x1+β2x2+β3x1x2

where

y = Firm’s 3-year buy-and-hold return rate (%)

x1 = {1 if stock split prior to acquisition, 0 if not}

x2 = {1 if firm’s discretionary accrual is high, 0 if discretionary accrual is low}

a. In terms of the β’s in the model, what is the mean buy and- hold return rate (BAR) for a firm with no stock split and a high discretionary accrual (DA)?

b. In terms of the β’s in the model, what is the mean BAR for a firm with no stock split and a low DA?

c. For firms with no stock split, find the difference between the mean BAR for firms with high and low DA. (Hint: Use your answers to parts a and b.)

d. Repeat part c for firms with a stock split.

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Consider relating E(y) to two quantitative independent variables x1 and x2.

  1. Write a first-order model for E(y).

  2. Write a complete second-order model for E(y).

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