'3 Run a regression analysis on the following bivariate set of data with y as the response variable, X Y 52.5 68.3 72.7 5.1 58.3 29.7 61.1 70.1 55 80.3 71 .7 38.6 77.3 -34.5 67.6 0.5 71 10.4 63.2 -O.8 40.2 72.1 43.7 52.1 Find the correlation coefficient and report it accurate to three decimal places. r= What proportion of the variation in y can be explained by the variation in the values of x? Report answer as a percentage accurate to one decimal place. (If the answer is 0.84471, then it would be 84.5%. . ,you would enter 84.5 without the percent symbol.) rZ= 96 0 Question 14 B 0/1 pt '0 2 Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as 'y = -58.63 X + 94.86' and the 'r = -0.934'. What proportion of the variation in y can be explained by the variation in the values of x? r2 = 96 Report answer as a percentage accurate to one decimal place. 0 Question 15 B 0/1 pt '0 2 l5 Let 'f(x)' be the height of a maple tree in inches and .x' the number of years since 2000. A linear model for the data is 'f(x) = 9.44 x + 84.1821 A :" //' / /6 ' 015 A) To the nearest inch, estimate the height of the maple tree in 2011. inches B) Use the equation to find the year in which the tree will be 241 inches tall. OW Bonmoz l g The following table shows retail sales in drug stores in billions of dollars in the U.S. for years since 1995. Year Retail Sales 0 85.851 3 108.426 6 141.781 9 169.256 12 202.297 15 222.266 Let 'S(t)' be the retails sales in billions of dollars in t years since 1995. A linear model for the data is 'F(t) = 9.44 t + 84.1822 220 /' 210 200 190 180 170 160 / 150 140 130 / 120 110 g 100 90 30' (113 Use the above scatter plot to decide whether the linear model fits the data well. The function is not a good model for the data The function is a good model for the data. Estimate the retails sales in the U. S. in 2012. Use the model to predict the year in which retails sales will be $234 billion. . Question 17 billions of dollars. Bei1pt'02 several Northwestern states. 'x' 11.5 8.6 6.9 3.9 2.6 2.3 2.1 0.5 y 14.1 11.6 9.9 7.6 6 6.3 5.9 4.2 'x' = thousands of automatic weapons 'y' = murders per 100,000 residents , 7 The table below shows the number of state-registered automatic weapons and the murder rate for This data can be modeled by the equation 'y=0.88 x +3.96. ' Use this equation to answer the following; A) How many murders per 100,000 residents can be expected in a state with 1 .5 thousand automatic weapons? Answer = Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 7.5 thousand automatic weapons? Answer = Round to 3 decimal places. 0 Question 13 80/1 pt '0 z The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. 'x' 11.4 8.5 6.7 3.3 2.4 2.2 2.1 0.7 y 13.7 11.5 10 7 6.2 5.9 6.1 4.3 'x' = thousands of automatic weapons 'y' = murders per 100,000 residents This data can be modeled by the equation 'y=0.86 x +4.06. ' Use this equation to answer the following; Special Note: I suggest you verify this equation by performing linear regression on your calculator. A) How many murders per 100,000 residents can be expected in a state with 4.5 thousand automatic weapons? Answer = Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 2 thousand automatic weapons? Answer = Round to 3 decimal places. | '1 A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y:ax+b a: 79 . 837 11:35 . 245 r2 . 427716 r: 79 . 654 Use this to predict the number of situps a person who watches 12. 5 hours of TV can do (to one decimal place) 0 Question 20 E\"; 0/1 pt f) 2 A regression was run to determine if there is a relationship between hours of TV watched per day, 'x' , and number of sit-ups, 'y', a person can do in a minute. The results of the regression were: y=ax+b a=0.786 b=26 . 613 Use this to predict the number of sit-ups a person who watches '12' hours of TV can do in a minute, Round to the nearest whole number. 0 Question 21 B 0/1 pt '0 2 \\Run a regression analysis on the following bivariate set of data with y as the response variable. X Y 17.6 24.8 22.6 33.3 26,8 23.5 Z7 37.7 15,8 73.5 15.7 65.9 29,1 14.2 35.5 31.1 553 2.4 20.4 36.1 83 72.1 24.3 26.1 Find the correlation coefficient and report it accurate to three decimal places. r: What proportion of the variation in y can be explained by the variation in the values of x? Report answer as a percentage accurate to one decimal place. (If the answer is 0.84471y then it would be 84.5%...you would enter 845 without the percent symbol.) r2 = 96 Based on the data, calculate the regression line (each value to three decimal places) y: x1- Predict what value (on average) for the response variable will be obtained from a value of 46.7 as the explanatory variable, Use a significance level of 'alpha = 0.05' to assess the strength of the linear correlation. What is the predicted response value? (Report answer accurate to one decimal place.) y: 35 If the equation of the regression line that relates hours per week spent in the tutor lab, 'x' , to GPA, 'y' , is 'y = 2.1 + 0,28x' , then the best prediction for the GPA of students who never go to the tutor A 3' Statistics students in Oxnard College sampled 9 textbooks in the Condor bookstore and recorded the number of pages in each textbook and its cost. The bivariate data is shown below, lab is 2.1. Number of Pages 1 'x': Cost! 'y'! 703 47.18 false 543 29.58 true 322 35.32 357 33.42 850 47 650 39 459 41.54 916 61.96 441 38.46 Click to Copy-and-Paste Data A student calculates a linear model 'y' = 'x' + . (Please show your answers to two decimal places) Use the model above to estimate the cost when number of pages is 396 Cost = 5 (Please show your answer to 2 decimal places.) 0 Question 23 B 0/1 pt '0 Z If the equation of the regression line for hours 'x' spent cycling in the summer and hours 'y' spent working in the summer is 'hat(y) = -0.7x + 42' , then as the number of cycling hours increases, the number of work hours tends to decrease. true false 0 Question 24 B 0/1 pt E) 2 If the equation of the regression line that relates income in dollars of student's parents, 'x' , with cost in dollars of tuition, 'y' , is 'haty = 8000 + 0.02x' , then the slope tells us that for every dollar increase in tuition, student's parent's income tends to be 2 cents higher. true false 0 Question 25 B 0/1 pt '0 Z