Find the equation of the regression linethen construct a scatter plot of the data and draw the regression linethen use the regression equation to predict the value of y for each of the given x values, if meaningful. If the x-values is not meaningful to predict the value of y, explain why not.A) x=5 wins B) x=10 wins C) x=21 wins D) x=15 wins The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season.| Wins, x | Earned run average, y ||---------|-----------------------|| 9 | 5.03 || 11 | 4.74 || 12 | 4.27 || 14 | 3.74 || 16 | 3.87 || 17 | 3.67 || 18 | 2.68 || 20 | 2.79 |i) Find the equation of the regression line.ii) Then construct a scatter plot of the data and draw the regression line.iii) Then use the regression equation to predict the value of y for each of the given x-values; if meaningful. If the x-value is not meaningful to predict the value of y, explain why not.- A) x = 5 wins- B) x = 10 wins- C) x = 21 wins- D) x = 15 wins

Steps to construct scatter plot in Excel: Enter the data for x and y in Excel sheet>Select the columns of x and y> Insert>“Insert scatter or bubble chart” option>Scatter under Charts>Under chart elements, select Exponential Trend line. Excel Output: From the output, the regression equation is, Y=-0.1849X+6.3553. A) x=5 wins Y=-(0.1849*5)+6.3553 =5.4308 B) x=10 wins Y=-(0.1849*10)+6.3553 =4.5063 C) x=21 wins Y=-(0.1849*21)+6.3553 =2.4724 D) x=15 wins Y=-(0.1849*15)+6.3553 =3.5818

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then use the regression equation to predict the value of y for each of the given x values, if meaningful. If the x-values is not meaningful to predict the value of y, explain why not. A) x=5 wins B) x=10 wins C) x=21 wins D) x=

then use the regression equation to predict the value of y for each of the given x values, if meaningful. If the x-values is not meaningful to predict the value of y, explain why not. A) x=5 wins B) x=10 wins C) x=21 wins D) x=

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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The table shows the amounts of crude oil (in thousands of barrels per day) produced by a certain country and the amounts of crude oil (in thousands of barrels per day) imported by the same country for seven years. The equation of the regression line is y =-1.364x+17,178.20. Complete parts (a) and (b) below. Produced, x Imported, y 5,744 5,554 5,439 5,188 5,136 5,067 D 9,132 9,677 10,017 10,193 10,149 10,075 5,756 9,328 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.)
The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Which of the following is the best interpretation of the coefficient of determination r2? About 37% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 65% of the variation in foot length is accounted for by the linear relationship formed with the arm span. About 63% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 63% of the variation in foot length is accounted for by the linear relationship formed with the arm span.
The table shows the lengths and weights of seven muskies captured by the Department of Natural Resources in Catfish Lake in Eagle River, Wisconsin. 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. Musky 1 2 3 4 5 6 7 Length (in.) 26 27 29 33 35 36 38 Weight (lb) 5 8 9 12 14 14 19
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
Use the given data set to answer parts (a) and (b). a. Find the regression equation for the data points. X 5 b. Graph the regression equation and the data points. y -1 10 -10 y B. 10 -10- C. a. Find the regression equation for the data points. ŷ-0 (Use integers or decimals for any numbers in the expression. Round to two decimal places as needed.) b. Graph the regression equation and the data points. O A. 10 T -10- 1 2 -1 3 327 D. -10 4 y 4 28 0
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
a. Using the pairs of values for all 10 points, find the equation of the regression line. b. After removing the point with coordinates (2,3), use the pairs of values for the remaining 9 points and find the equation of the regression line. c. Compare the results from parts (a) and (b).
H. Find the slope and y-intercept of each regression line. Then, determine if the correlation between the variables is positive or negative. (12 points) Regression Line Equation 1. Y = 1.751X – 21.722 Slope y-intercept Kind of Correlation 2. Y = -221.943X+65.434 3. Y = -82.455X –314.986 4. Y = 0.997X + 0.168
search Refer to the data set: y X -3 -2 =1 -00 .......... 1 8 1 7 −IN 01 1 2 2 4 Part a: Make a scatter plot and determine which type of model best fits the data. Part b: Find the regression equation. Part c: Use the equation from Part b to determine y when x = 5 For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac). BIUS Paragraph V Arial h V © O Click Save and Submit to save and submit. Click Save All Answers to save all answers. 10pt DELL
Below is the output from regression. Use the p-value and decide if the equation is good to use for forecasting. Group of answer choices A.) p-value = 82 - equation is good to use B.) p-value = 0.15 - equation is not good to use C.) p-value = 0.18 - equation is not good to use D.) p-value = -16 - equation is good to use
B) What is the equation of the regression line for the set of 9 points?
n order for applicants to work for the foreign-service department, they must take a test in the language of the country where they plan to work. The data below shows the relationship between the number of years that applicants have studied a particular language and the grades they received on the proficiency exam. Find the equation of the regression line for the data. given Number of years, x 4 5 3 6 2 7 3 Grades on test, y 61 68 75 82 73 90 58 93 72 O A. y 6.910x+46.261 O B. -46.261x +6.910 O C. =6.910x-46.261 O D. = 46.261x-6.910 Next Time Remaining: 01:02:25 74°F Mostly 五 TTL