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 758 621 518 510 492 (a) x = 501 feet 483 (h) Y = 650 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 758 621 518 510 492 (a) x = 501 feet 483 (h) Y = 650 feet

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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An instructor asked a random sample of eight students to record their study times at the beginning of a course. She then made a table for total hours studied (x) over 2 weeks and test score (y) at the end of the 2 weeks. The table is given below. Complete parts (a) through (f). x 10 13 10 18 6 15 16 21 y 93 79 81 74 85 81 85 80 a. Find the regression equation for the data points. b. Graph the regresson equation c. Describe the apparent relationship between the two variables. d. Identify the predictor and response variables. e. Identify outliers and potential influential observations. f.Predict the score for a student that studies for 17 hours.
The table shows the approximate chirping rate at various temperatures for one type of cricket. Use the linear regression feature on a graphing calculator to determine an equation of the line that best fits the data. Round to the hundredths. ⒸEncikAn/Shutterstock.com X Temperature (°F) 50 60 70 80 100 Chirps per Minute 20 80 115 150 250
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.…
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 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. 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)
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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.)
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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 Sodium, y (a) x= 150 calories (c) x= 120 calories (b) x= 90 calories (d) x=60 calories 160 180 130 130 80 190 415 465 350 380 270 540 (c) Predict the value of y for x= 120. Choose the correct answer below O A. 347 151 O B. 279.801 O C. 414.501 O D. not meaningful (d) Predict the value of y for x= 60. Choose the correct answer below. O A. 414.501 O B. 212.451 tes O C. 279.801
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 150 180 120 130 90 190 P (a)x= 170 calories (c) x 140 calories (b)x= 100 calories (d) x = 210 calories Sodium, y 430 480 350 370 290 530 REED Find the regression equation. ŷ=x+0) (Round to three decimal places as needed.) 4
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 Test score, y 4 47 (a) x=3 hours (c) x= 13 hours (b) x= 2.5 hours (d) x= 3.5 hours 5 6 40 45 52 63 72 Find the regression equation. y=x+ (O (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)
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