saint GBA334 quiz 2- 100% correct

 

saint GBA334 quiz 2- 100% correct

Quiz 2

Question 1. 1. A large school district is reevaluating its teachers’ salaries. They have decided to use regression analysis to predict mean teachers’ salaries at each elementary school. The researcher uses years of experience to predict salary. The resulting regression equation was:Y = 23,313.22 + 1,210.89X, where Y = salary, X = years of experienceBased on this equation, by how much could a teacher expect his or her salary to increase for every additional tear of service?

(Points : 3)




Question 2. 2. A large school district is reevaluating its teachers’ salaries. They have decided to use regression analysis to predict mean teachers’ salaries at each elementary school. The researcher uses years of experience to predict salary. The resulting regression equation was:Y = 23,313.22 + 1,210.89X, where Y = salary, X = years of experienceAssume a teacher has ten years of experience.

What is the forecasted salary?

(Points : 3)




Question 3. 3. A large school district is reevaluating its teachers’ salaries. They have decided to use regression analysis to predict mean teachers’ salaries at each elementary school. The researcher uses years of experience to predict salary. The resulting regression equation was:Y = 23,313.22 + 1,210.89X, where Y = salary, X = years of experienceAssume a teacher has five years of experience. What is the forecasted salary?

(Points : 3)




Question 4. 4. The coefficients of each independent variable in a multiple regression model represent slopes. (Points : 3)


Question 5. 5. Which of the following statements is false concerning the hypothesis testing procedure for a regression model? (Points : 3)





Question 6. 6. A scatter diagram is a graphical depiction of the relationship between the dependent and independent variables. (Points : 3)


Question 7. 7. Time-series models attempt to predict the future by using historical data. (Points : 3)


Question 8. 8. Scatter diagrams can be useful in spotting trends or cycles in data over time. (Points : 3)


Question 9. 9. If computing a causal linear regression model of Y = a + bX and the resultant r2 is very near zero, then one would be able to conclude that: (Points : 3)




Question 10. 10. An air conditioning and heating repair firm conducted a study to determine if the average outside temperature, thickness of the insulation, and age of the heating equipment could be used to predict the electric bill for a home during the winter months in Houston, Texas. The resulting regression equation was:Y = 256.89 – 1.45X1 – 11.26X2 + 6.10X3, where Y = monthly cost, X1 = average temperature, X2 = insulation thickness, and X3 = age of heating equipmentAssume December has an average temperature of 45 degrees and the heater is 2 years old with insulation that is 6 inches thick.

What is the forecasted monthly electric bill?

(Points : 3)