Identify whether the quadratic model is useful for establishing the relationship between plant height and effect of manganese (Mn). Test by using necessary hypotheses.

Question

The article "Earthmoving Productivity Estimation Using Linear Regression Techniques" (S. Smith, Journal of Construction Engineering and Management, 1999:133–141) presents the following linear model to predict earth-moving productivity (in m3 moved per hour): Productivity = - 297.877 + 84.787x, + 36.806x, + 151.680x, – 0.081x, – 110.517x5 - 0.267.x, – 0.016x,x, +0.107.x,x5 + 0.0009448x,x, – 0.244x;x, where X1 = number of trucks X2 = number of buckets per load X3 = bucket volume, in m³ X4 = haul length, in m X5 = match factor (ratio of hauling capacity to loading capacity) X6 = truck travel time, in s If the bucket volume increases by 1 m², while other independent variables are unchanged, can you determine the change in the predicted productivity? If so, determine it. If not, state what other information you would need to determine it. b. If the haul length increases by 1 m, can you determine the change in the predicted productivity? If so, determine it. If not, state what other…

Answer 1

Question

Chapter 13, Problem 75SE

a.

To determine

Identify whether the quadratic model is useful for establishing the relationship between plant height and effect of manganese (Mn).

Test by using necessary hypotheses.

b.

To determine

Identify whether the quadratic predictor should be eliminated.

c.

To determine

Find the expected height when the manganese takes 10μM using the 90% confidence interval.

Expert Solution & Answer

Trending nowThis is a popular solution!

See solution

Check out sample textbook solution

Students have asked these similar questions

The article "Earthmoving Productivity Estimation Using Linear Regression Techniques" (S. Smith, Journal of Construction Engineering and Management, 1999:133–141) presents the following linear model to predict earth-moving productivity (in m3 moved per hour): Productivity = - 297.877 + 84.787x, + 36.806x, + 151.680x, – 0.081x, – 110.517x5 - 0.267.x, – 0.016x,x, +0.107.x,x5 + 0.0009448x,x, – 0.244x;x, where X1 = number of trucks X2 = number of buckets per load X3 = bucket volume, in m³ X4 = haul length, in m X5 = match factor (ratio of hauling capacity to loading capacity) X6 = truck travel time, in s If the bucket volume increases by 1 m², while other independent variables are unchanged, can you determine the change in the predicted productivity? If so, determine it. If not, state what other information you would need to determine it. b. If the haul length increases by 1 m, can you determine the change in the predicted productivity? If so, determine it. If not, state what other…

a) We conduct a regression of size on hhinc, owner, hhsize, hhsize2,and hhsize3. We do not include the constant. The regression output is reported in Table 3. Would you conclude that the home size increases with the household size? Interpret the sign and magnitude of the estimated coefficients of hhsize1, hhsize2, and hhsize3.

Given: A regression of ln(wage) on educ, exper, exper2, female, married, numdep and two interaction terms female ∗ edu and female ∗ married. (For the interaction terms I multiplied female data x edu data and so forth) Question: What does the coefficient on the interaction term measure? Interpret the coefficients on the interaction term, female ∗ edu and female ∗ married.