Which inductor shows how well a regression line fits through the scatter of data

Question

Which inductor shows how well a regression line fits through the scatter of data points? A) Durbin-Watson test B) t-test C) R^2 D) F-test Answer the following question(s) based on the following regression equation (Standard errors in parenthesis, m = 150 Q_D = 1000 - 50P_A + 10P_B + where Q_D = demanded of good A. P_A = of good A. P_B = price of a competing good B, and l = per capital Using the "rule 2", which of the following variables can be deemed statistically significant? A) l B) P_B C)P_A D) All of the above E) None of the above For the regression equation Q = 100 - 10X + 0.25X^2, which of the following statements is true? A) When X increases by 10 units, Q decreases by 1 unit. B) The change in Q associated with a one unit increase in X depends on the initial level of X. C) X^2 is the more important variable because it is positive. D) When X decreases by one unit, Q decreases by 10 units. Answer the following question(s) based on the following regression equation (Standard errors in parenthesis, m = 150 where Q is the quantity demanded of good A; P_A = $10, price of good A; P_B = price of good B; I = 512.050, per capita in $20,000, monthly advertising expenditures. Which of the variables does not past the t-test at the OS level of significance? A) 1 B) A C) P_A D)P_B E) All the variables pass the t-test As a researcher, which aspect of the results would be of greatest concern? A) the poor fit of the regression line B) the relatively low impact of the competitor's price C) the fact that not all of the variables are statistically significant D) the negative value of the constant (i.e., .500) As the manager of good A, which of the following would be of greatest concern (based on the regression results above)?

Explanation / Answer

Ans 7. C) R-sq;

It is the measure for regression fit line.

Ans 8. C) PA

REASON:

Formula:

Ans. 9. b) increase in Q depends on initial value of x.

Ans 10. E) all the variables are significant.

11. a) poor fit of .12

coeff SE t-stat P-value PA 50 20 2.5 0.013533 PB 10 7 1.428571 0.155278 I 0.05 0.04 1.25 0.213313

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