The equation used to predict annual cauliflower yield (in pounds per acre) is y = 23,482 +4.455x, -4.602x,, where x, is the number of acres planted and x, is the number of acres harvested. Use the multiple regression equation to predict the y-values for the values of the independent variables. (a) x, = 37,000, x, = 37,400 (b) x, = 38,800, X2 = 39,000 (c) x, = 39,800, X2 = 39,900 (d) x, = 43,000, x = 43,100 (a) The predicted yield is pounds per acre. (Round to one decimal place as needed.) (b) The predicted yield is pounds per acre. (Round to one decimal place as needed.) (c) The predicted yield is pounds per acre. (Round to one decimal place as needed.) (d) The predicted yield is pounds per acre.

= In a statistics course, a linear regression equation was computed to predict the final-exam score from the score on the first test. The equation as y 10+ 0.75x where y is the final-exam score and x is the score on the first test. Parvez scored 80 on the first test. What is the predicted value of the Parvez's score on the final exam? Parvez scored 60 on the final exam. What is the value of the residual?

The linear regression equation for predicting systolic blood pressure from age is as follows: y = 42 + 2.5x . Find the residual for a person who is 21 years of age with a systolic blood pressure of 91.9.

Based on the data from 6 students, the regression equation relating number of hours of preparation (x) and test score (y) is y=67.3 + 1.07x . What is the best predicted test score for a student who spent 120 minutes preparing for the test?

The equation used to predict annual cauliflower yield​ (in pounds per​ acre) is y=24,596+4.423x1−4.772x2​, where x1 is the number of acres planted an x2 is the number of acres harvested. Use the multiple regression equation to predict the​ y-values for the values of the independent variables.

The age and height (in cm) of 400 adult women from Bolivia were measured. A researcher wants to know if age has any effect on height. A linear regression is carried out in Minitab and the following output obtained. Coefficients Term Constant Age (a) Write down the regression model. (b) Interpret the regression coefficient for the fitted model. (c) Use the output from Minitab to explain if the age of a participant affects their height. Percent (d) The normal probability plot of the residuals from this regression model is given below. Do the assumptions of the regression model seem reasonable? Justify your answer. 99.9 8 28 22299229 88 Coef SE Coef 152.94 7.69 0.022 0.231 01 -100 T-Value P-Value VIF 19.90 0.000 0.10 0.924 1.00 -50 Normal Probability Plot (response is Height) 0 Residual 50 ***** 100 150

The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thousands of barrels per day) imported by a country, for the last 7 years. Construct and interpret a 98% prediction interval for the amount of oil imported by the country and the amount of oil produced by the country is 5,483 thousand barrels per day. The equation of the regression line is y = -1.194x + 16,234.906

A regression analysis between cost to build a clinic (in dollars) and clinic size (in square foot) resulted in the following equation: y=75+6x. This implies that if the clinic size is 800 square feet, then the cost to build a clinic (in dollars) is?

You run a linear regression to predict BMI (body mass index) from average minutes of physical activity per day. You calculate the slope of the regression to be -.054. Interpret the slope in terms of the independent and dependent variables.

The table shows the number of goals allowed and the total points earned (2 points for a win, and 1 point for an overtime or shootout loss) by 14 ice hockey teams over the course of a season. The equation of the regression line is ŷ= -0.556x+217.766. Use the data to answer the following questions. (a) Find the coefficient of determination, 12, and interpret the result. (b) Find the standard error of the estimate, Se, and interpret the result. 213 213 223 226 259 266 281 202 210 205 226 207 259 239 D Goals Allowed, x Points, y 109 109 102 91 88 80 52 105 107 98 95 85 68 66 (a)² = (Round to three decimal places as needed.) Interpret the coefficient of determination. Select the correct choice below and fill in the answer box to complete your choice. (Round to one decimal place as needed.) OA. About OB. About (b) Se = % of the variation in points earned can be explained by the relationship between number of goals allowed and points earned. The remaining variation is unexplained. % of the…