Compute the least-squares regression equation for the given data set. Use a TI-84 calculator. Round the slope and y-intercept to at least four decimal places. 4. 1 7. 6. 6. 1 3 4 Send data to Excel Regression line equation: y =

Compute the least-squares regression equation for the given data set. Use a TI-84 calculator. Round the slope and y-intercept to at least four decimal places. 4. 1 7. 6. 6. 1 3 4 Send data to Excel Regression line equation: y =

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 40 inches. Is the result close to the actual weight of 352 pounds? Use a significance level of 0.05. Chest size (inches) *Weight (pounds) 44 54 328 528 41 55 39 51 418 580 296 503 Click the icon to view the critical values of the Pearson correlation coefficient r. - What is the regression equation? x (Round to one decimal place 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 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…
The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best-predicted temperature for a time when a bug is chirping at the rate of 3000chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 1004 952 1237 1116 1177 1249 Temperature (°F) 83.1 76 95.1 87.5 92.1 88.4 What is the regression equation? (^ over y)=_____+_____x (Round the x-coefficient to four decimal places as needed. Round the constant to two decimal places as needed.) What is the best-predicted temperature for a time when a bug is chirping at the rate of 3000chirps per minute? The best-predicted temperature when a bug is chirping at 3000 chirps per minute is ____°F. (Round to one decimal place as needed.) What is wrong with this predicted value? Choose the correct answer below. A. It is…
Report the equation of the regression line and interpret it in the context of the problem
Find the regression equation Student 1 4 5 6 7 8 9 10 Placement Exam 83 89 92 77 81 81 85 85 87 84 GWA 83 85 90 80 83 85 87 84 90 85 Select the correct response: y=35.39-0.5901x y=35.39x+0.5901 y=0.5901x-35.39 y=35.39+0.5901x 3. 2.
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. 170 480 Calories, x Sodium, y 560 Find the regression equation. ŷ=x+ (Round to three decimal places as needed.) Choose the correct graph below. OA. 0ff 0 200 150 430 Calories 130 320 a 130 380 O B. 560 0 80 250 200 G Calories (a) Predict the value of y for x = 160. Choose the correct answer below. OA. 390.863 OB. 440.983 OC. 591.343 O D. not meaningful (b) Predict the value of y for x = 90. Choose the correct answer below. 190 510 (a) x (c) x 160 calories 140 calories O C. A 560+ 0-T 0 200 Calories (b) x = 90 calories (d) x = 220 calories OD. 560- 0 200 Calories Q
Fill in the blanks. a. Multicollinearity is considered to be severe if the VIF for one or more predictor variables is ______. or greater. b. If the coefficient of multiple determination for the regression of the predictor variable x11 on all the other predictor variables in a regression equation is 0.6, then the VIF for x1 is ______. c. The effect of multicollinearity in a polynomial regression analysis can be reduced by ______. the predictor variable.
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 130 380 80 270 (a) x= 150 calories (c) x-120 calories 190 160 415 180 465 130 350 (b) X3D90 calories (d) x= 60 calories 540 (a) Predict the value of y for x= 150. Choose the correct answer below. O A. 212.451 B. 347.151 C. 414.501 O D. not meaningful (b) Predict the value of y for x= 90. Choose the correct answer below. O A. 212.451 O B. 347.151 es OC. 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. (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
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 58 inches. Is the result close to the actual weight of 662 pounds? Use a significance level of 0.05. Chest size (Inches) 46 57 53 41 40 40 Weight (Pounds) 384 580 542 358 306 320
Compute the least-squares regression equation for the given data set. Round the slope and yFintercept to at least four decimal places. 4 y 7. 3. Send data to Excel Regression line equation: y =|