The Kentucky Department of Agriculture is concerned about the number of acres of farmland being withdrawn from farming. The department would like to propose new legislation to prevent this but wants to show the legislature what would happen if it does not act. Drew Johnson, the department’s statistician, regresses the number of acres used for farming in the state on time. Johnson finds the following: Model R R Square Adjusted R Square Std. Error of the Estimate 1 .943a .890 .795 3.2875 Predictors: (Constant), Number of Years Model   Sum of Squares df Mean Square F Sig. 1 Regression 1378.458 1 1378.458 141.149 .000a     Residual 478.567 49 9.766 9.766       Total 1857.025 50         Predictors: (Constant), Number of Years Dependent Variable: Acres (in Millions)   Unstandardized   Standardized       B Std. Error Beta t Sig. 1 constant 2.743 .357   7.683 .000 year -.027 .0007 -.025 -38.571 .000 Dependent Variable: Acres (in Millions) What is the IV? What is the DV?  How strong is the relationship? From the results shown above, write the regression equation. How many acres of farmland will be lost in the next 10 years if the legislature does not act and if past practices continue?

1,280 people33,264 people51,975 people166,320 people

For this problem, carry at least four digits after the decimal in your calculations. Answers may vary slightly due to rounding.A random sample of medical files is used to estimate the proportion p of all people who have blood type B.

You measure the length of 11 bullfrogs (Lithobates (=Rana) catesbeiana), and then measure how for each frog can jump. You get the following results (size in mm, jump distance in cm). Size 155 127 136 135 158 145 136 172 158 162 162 Distance 71.0 70.0 100.0 120.0 103.3 116.0 109.2 105.0 112.5 114.0 122.9 You find the following results: SSx = 2,094.55 SSy = 3,218.99 SScp = 731.36 n = 11 ¯y = 103.99 ¯x = 149.64 SSresid = 2,963.61 a) Give the equation of the least squares line. b) Give both the test statistic and the table value. Make sure you give H0, H1, α, etc. and state your conclusion. c) Make a scatterplot of these data and fit the least squares line. d) Make a residual plot of these data and comment on it. e) Calculate R 2 and explain. Is R 2 even appropriate here (what is your answer to (b)?)