Listed below are the heights (cm) of winning presidential candidates and their main opponents from several recent pres elections. Find the regression equation, letting president be the predictor (x) variable. Find the best predicted height of given that the president had a height of 188 cm. How close is the result to the actual opponent height of 175 cm? President 178 177 188 188 191 175 185 183 188 180 183 188 173 169 173 177 185 175 Opponent The regression equation is y=+ (x. (Round the v-intercent to the nearest integer as needed Round the slope to three decimal places as needed)
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- Two variables have a positive linear correlation. Is the slope of the regression line for the variables positive or negative? A. The slope is negative. As the independent variable increases the dependent variable also tends to increase. B. The slope is negative. As the independent variable increases the dependent variable tends to decrease. C. The slope is positive. As the independent variable increases the dependent variable also tends to increase. D. The slope is positive. As the independent variable increases the dependent variable tends to decrease.Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The number of hours 6 students spent for a test and their scores on that test are shown below. Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The number of hours 6 students spent for a test and their scores on that test are shown below. Hours spent studying, x 0 2 2 3 5 5 Test score, y 38 45 52 49 61 73 (a)x= 2 hours (b)x=4.5 hours (c)x=13 hours (d)2.5 hours Find the regression…Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height, x Stories, y A 60- 0 775 53 Q 619 47 519 46 OB. 508 42 Find the regression equation. y = x+ (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. Q. A. 60 0 491 37 800 800 Height (feet) (n) Brodict the value of x for x=503. Choose the correct answer below. Height (feet) 474 36 D ... (a) x = 503 feet (c) x 310 feet OC. 800 0 Height (feet) Q www. (b)x=642 feet (d) x = 730 feet OD. 60- 0- 0 800 Height (feet)
- Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height, x Stories, y 762 51 621 46 515 45 508 42 491 39 480 36 (a) x = 502 feet (c) x = 315 feet Find the regression equation. ŷ=x+ (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) (b) x = 645 feet (d) x = 731 feetFind the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x 150 180 130 120 90 190 (a) x=160 calories (b) x=100 calories Sodium, y 430 480 320 360 290 550 (c) x=140 calories (d) x=50 calories Find the regression equation. y=nothingx+(nothing) (Round to three decimal places as needed.) Choose the correct graph below. A. 02000560CaloriesSodium (mg) A scatterplot has a horizontal axis labeled "Calories" from 0 to 200 in increments of 20 and a vertical axis labeled "Sodium (in milligrams)" from 0 to 560 in increments of…Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x 130 130 350 370 150 (a) x 160 calories (b)x= 100 calories Sodlum, y (c) x 140 calories (d) x=200 calories Find the regression equation. (Round to three decimal places as needed.) Choose the correct graph below. OA 560 Q Q 200 G Calories (a) Predict the value of y for x = 160. Choose the correct answer below. OA. 393.094 OB. 440.954 OC. 536.674 OD. not meaningful (b) Predict the value of y for x= 100. Choose the correct answer below. OA 297.374 OB. 536.674 OC. 393.094 OD. not meaningful (c) Predict the value of y for x = 140. Choose the correct answer below. OA 297.374 OB.…
- The following table gives the data for the grades on the midterm exam and the grades on the final exam. Determine the equation of the regression line, y = bo + b₁x. Round the slope and y-intercept to the nearest thousandth. Grades on Midterm and Final Exams Grades on Midterm 66 68 71 86 78 85 62 82 79 61 Grades on Final 90 63 82 96 72 83 79 91 84 65Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height, x Stories, y 758 621 518 510 492 | 483 | 51 47 46 43 39 36 Find the regression equation. y = ☐ X+ (a) x = 503 feet (c) x = 802 feet (b) x = 649 feet (d) x = 728 feet (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city.
- Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. 483 Height, x Stories, y 772 628 518 508 51 48 45 42 496 37 (a) x=499 feet (c) x=315 feet (b)x=639 feet (d) x = 732 feet 35 Find the regression equation. ŷ=x+ (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. O C. OB. O D. OA. Q Q ↓ 0 0 Height (feet) Height (feet) (a) Predict the value of y for x = 499. Choose the correct answer below. OA. 51 OB. 40 60+ 0- 800 60+ 0- 800 Q A 60- → 0 Height (feet) 800 60- 0- 800 0 Height (feet)Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The number of hours 6 students spent for a test and their scores on that test are shown below. Hours spent studying, x 1 2 2 3 4 6 Test score, y 39 44 52 47 64 70 (a)x=2hours (b)x=3.5hours (c)x=13hours (d)x=1.5hours Find the regression equation. y=______ x+ (_____) (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. (a) x 503 feet (c) x = 318 feet (b) x = 649 feet (d) x = 724 feet 766 494 484 520 44 620 508 Height, x Stories, y 51 46 43 39 38 (c) Predict the value of y for x=318. Choose the correct answer below. O A. 34 B. 50 O C. 47 O D. not meaningful (d) Predict the value of y for x=724. Choose the correct answer below. O A. 34 O B. 41 50