Questions from Engineering Statistics

Q: Consider Example 12.3 on page 447. Compare the two

Consider Example 12.3 on page 447. Compare the two competing models. First order: yi = β0 + β1x1i + β2x2i + €i, Second order: yi = β0 + β1x1i + β2x2i+ β11x21i + β22x22i + β12x1ix2i + i. Use R2adj in y...

Q: In Example 12.8, a case is made for eliminating

In Example 12.8, a case is made for eliminating x1, powder temperature, from the model since the P-value based on the F-test is 0.2156 while P-values for x2 and x3 are near zero. (a) Reduce the model...

Q: Suppose that the time to failure T of a certain hinge is

Suppose that the time to failure T of a certain hinge is an exponential random variable with probability density f(t) = θe−θt, t>0. From prior experience...

Q: Consider the data of Exercise 12.13 on page 452.

Consider the data of Exercise 12.13 on page 452. Can the response, wear, be explained adequately by a single variable (either viscosity or load) in an SLR rather than with the full two-variable regres...

Q: For the data set given in Exericise 12.16 on page

For the data set given in Exericise 12.16 on page 453, can the response be explained adequately by any two regressor variables? Discuss. Exericise 12.16: An engineer at a semiconductor company wants...

Q: A study was done to assess the cost effectiveness of driving a

A study was done to assess the cost effectiveness of driving a four-door sedan instead of a van or an SUV (sports utility vehicle). The continuous variables are odometer reading and octane of the gaso...

Q: A study was done to determine whether the gender of the credit

A study was done to determine whether the gender of the credit card holder was an important factor in generating profit for a certain credit card company. The variables considered were income, the num...

Q: Consider the “hang time” punting data given in Case Study

Consider the “hang time” punting data given in Case Study 12.2, using only the variables x2 and x3. (a) Verify the regression equation shown on page 489. (b) Predict punter hang time for a punter wi...

Q: For the data of Exercise 12.15 on page 452,

For the data of Exercise 12.15 on page 452, use the techniques of (a) forward selection with a 0.05 level of significance to choose a linear regression model; (b) backward elimination with a 0.05 le...

Q: Use the techniques of backward elimination with α = 0.05

Use the techniques of backward elimination with α = 0.05 to choose a prediction equation for the data of Table 12.8.