Suppose there is a significant correlation between two variables. Describe a case under which it might be inappropriate to use the linear regression equation for prediction

Hormone replacement therapy (HRT) is thought to increase the risk of breast cancer. The accompanying data on x percent of women using HRT and y breast cancer incidence (cases per 100,000 women) for a region in Germany for 5 years appeared in the paper *Decline in Breast Cancer Incidence after Decrease in Utilization of Hormone Replacement Therapy." The authors of the paper used a simple linear regression model to describe the relationship between HRT use and breast cancer incidence. HRT Use Breast Cancer Incidence 46.30 103.30 40.60 105.00 39.50 100.00 36.60 93.80 30.00 83.50 (a) What is the equation of the estimated regression line? (Round your numerical values to four decimal places.) 9= (b) What is the estimated average change in breast cancer incidence (in cases per 100,000 women) associated with a 1 percentage point increase in HRT use? (Round your answer to four decimal places.) cases per 100,000 women (c) What breast cancer incidence (in cases per 100,000 women) would be...

Please assist not sure of my anwer. It’s statistics.

what is a confidence coefficinent for a simple linear regression line whoes alpha =0.05 and line is y(hat)=-7.45-10x

If the Pearson correlation between X and Y is negative, then the regression equation will have a negative slope. true or false

What are the Standard Errors for Fixed Effects Regression?

The maintenance manager at a trucking company wants to build a regression model to forecast the time (in years) until the first engine overhaul based on four predictor variables: (1) annual miles driven (in 1,000s of miles), (2) average load weight (in tons), (3) average driving speed (in mph), and (4) oil change interval (in 1,000s of miles). Based on driver logs and onboard computers, data have been obtained for a sample of 25 trucks. A portion of the data is shown in the accompanying table. Time Miles Load Speed Oil 7.7 42.9 22.0 44.0 16.0 0.8 98.3 20.0 47.0 34.0 6.3 61.1 22.0 62.0 15.0 E Click here for the Excel Data File b. Estimate the regression model. (Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.) Time = Miles Load Speed oil + + d. What is the predicted time before the first engine overhaul for a particular truck driven 60,000 miles per year with an average load of 25 tons, an average driving speed of 53 mph, and 21,000 miles...

The Conde Nast Traveler Gold List for 2012 provided rating for the top 20 small cruise ships. The data from annual Readers’ Choice Survey are the overall scores(Y) each ship received based on several criteria, including Itineraries/Schedule (X1), Shore Excursions(X2), and Food/Dinning(X3). The estimated regression equation to predict the overall scores is Y= 35.6184+0.1105 X1+0.2445 X2+0.2474 X3. Part of the regression results is shown below. Coefficients Standard Error Intercept 35.6184 13.2308 Itineraries/Schedule(X1) 0.1105 0.1297 Shore Excursions(X2) 0.2445 0.0434 Food/Dinning(X3) 0.2474 0.0621 Use the T test to determine whether or not the coefficient of X1 is significant. Use Level of significance=.05? Be sure to state null and alternative hypotheses....

If the estimated intercept of the regression equation is negative, we can say the estimated correlation coefficient between the two variables is also negative. O True O False

A researcher plans to study the causal effect of police on crime using data from a random sample of U.K. counties. He plans to regress the county’s crime rate on the (per capita) size of the county’s police force. Explain why this regression is likely to suffer from omitted variable bias. Which variable would you add to the regression to controlfor important omitted variable? Determine whether the regression will likely over or underestimate the effect of police on the crime rate?

The adjusted R-squared accounts for the amount of variance explained while also adjusting for the number of independent variables in the linear regression equation. True or False

Hormone replacement therapy (HRT) is thought to increase the risk of breast cancer. The accompanying data on x = percent of women using HRT and y = breast cancer incidence (cases per 100,000 women) for a region in Germany for 5 years appeared in the paper "Decline in Breast Cancer Incidence after Decrease in Utilization of Hormone Replacement Therapy." The authors of the paper used a simple linear regression model to describe the relationship between HRT use and breast cancer incidence. t HRT Use Breast Cancer Incidence 46.30 40.60 39.50 36.60 30.00 103.30 105.00 100.00 93.80 83.50 (a) What is the equation of the estimated regression line? (Round your numerical values to four decimal places.) ŷ = (b) What is the estimated average change in breast cancer incidence (in cases per 100,000 women) associated with a 1 percentage point increase in HRT use? (Round your answer to four decimal places.) cases per 100,000 women (c) What breast cancer incidence (in cases per 100,000 women) would be...

The figure shows four identical conducting spheres that are actually well separated from one another. Sphere W (with an initial charge of zero) is touched to sphere A and then they are separated. Next, sphere W is touched to sphere B (with an initial charge of -30e) and then they are separated. Finally, sphere Wis touched to sphere C (with an initial charge of 44e), and then they are separated. The final charge on sphere W is 18e. What multiple of e gives the initial charge on sphere A? A B C W Number i Units This answer has no units +