Question;Question 1. Question;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;experience;Based on this equation, by how much could a teacher expect;his or her salary to increase for every additional tear of service?;$1,210.89X;$1,210.89;$1,210.89 + X;$23,313.22;Question 2. Question;Time-series models attempt to predict the future by using;historical data.;True False;Question 3. Question;When the significance level is small enough in the F-test;we can reject the null hypothesis that there is no linear relationship.;True;False;Question 4. Question;A scatter diagram is a graphical depiction of the relationship;between the dependent and independent variables.;True;False;Question 5. Question;Quiz2_Ques7_correlation_coefficient;Click here to view a pdf of this graphic.;The diagram above illustrates data with a;negative correlation coefficient.;zero correlation coefficient.;positive correlation coefficient.;none of the above.;Question 6. Question;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 equipment;Assume 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?;$111.88;$127.72;$136.28;$205.72;Question 7. Question;Quiz1_Ques10;A prediction equation for starting salaries (in $1,000s) and;SAT scores was performed using simple linear regression. In the regression;printout shown above, what can be said about the level of significance for the;overall model?;Click here to view the printout in Excel.;SAT is not a good predictor for starting;salary.;The significance level for the intercept;indicates the model is not valid.;The significance level for SAT indicates the;slope is equal to zero.;The significance level for SAT indicates the;slope is not equal to zero.;None of the above can be said about the level;of significance.;Question 8. Question;Which of the following is a technique used to determine;forecasting accuracy?;Exponential smoothing;Moving average;Regression;Delphi method;Mean absolute percent error;Question 9. Question;A judgmental forecasting technique that uses decision;makers, staff personnel, and respondents to determine a forecast is called;exponential smoothing.;the Delphi method.;jury of executive opinion.;sales force composite.;consumer market survey.;Question 10. Question;Which of the following statements is false concerning the;hypothesis testing procedure for a regression model?;The F-test statistic is used.;The null hypothesis is that the true slope;coefficient is equal to zero.;The null hypothesis is rejected if the;adjusted r2 is above the critical value;An? level must be selected.;The alternative hypothesis is that the true;slope coefficient is not equal to zero.
Paper#52622 | Written in 18-Jul-2015Price : $22