1. The ages (In years) and the numbers of hours of sleep in one night for seven adults.Complete the table below. ThenX35205942683875X =Σy =y7956584xyxy =x²[x² =a. Calculate the correlation coefficient r for the data above.b. Find the equation of the regression line for the data.c. Draw the regression line on the scatter plot for the data above.y²Ly =

Here the dependent variable (y) is the age and the independent variable (x) is no. of hours of…

Answered: a. Calculate the correlation…

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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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 Un ne conteui yrapii veIUW. O A. Stories A 60- Height (feet) OO ( 800 (a) Predict the value of y for x = 503. Choose the correct answer below. A. 40 OB. 47 O C. 50 O D. not meaningful (b) Predict the value of y for x = 652. Choose the correct answer below. 774 51 OA. 54 O B. 47 OC. 40 O D. not meaningful (c) Predict the value of y for x = 810. Choose the correct answer below. OA. 54 625 47 OA. 54 OB. 50 OC. 47 O D. not meaningful (d) Predict the value of y for x = 725. Choose the correct answer below. B. 40 ΕΛ 521 45 O B. Stories 60+ 508 41 0 Height (feet) 800 497 38 477…
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. (a) x= 160 calories (c) x = 140 calories (b) x = 100 calories (d) x= 200 calories 130 90 180 Calories, x Sodium, y 150 170 130 410 460 350 360 280 530 Find the regression equation. (Round to three decimal places as needed.)
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 572 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 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=nothing+nothingx (Round to one decimal place as needed.)
A. run a simple regression- dependent variable is Weeks, independent variable is Age. B. run a multiple regression with dependent variable weeks and independent variable-age, married, head, manager and sales. C. Create the regular and standardized residual plots for both. Please show the tables when entering values of the regression for both the outputs and the scatter plots.
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 78 70 84 97 82 75 75 88 67 76 89 79 88 100 Grades on Final 71 80 77 77 72 65
The datasetBody.xlsgives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (lb), Height (in), and circumference (cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist. We are interested in predicting body fat based on abdomen circumference. Find the equation of the regression line relating to body fat and abdomen circumference. Make a scatter-plot with a regression line. What body fat percent does the line predict for a person with an abdomen circumference of 110 cm? One of the men in the study had an abdomen circumference of 92.4 cm and a body fat of 22.5 percent. Find the residual that corresponds to this observation. Bodyfat Abdomen 32.3 115.6 22.5 92.4 22 86 12.3 85.2 20.5 95.6 22.6 100 28.7 103.1 21.3 89.6 29.9 110.3 21.3 100.5 29.9 100.5 20.4 98.9 16.9 90.3 14.7 83.3 10.8 73.7 26.7 94.9 11.3 86.7 18.1 87.5 8.8 82.8 11.8 83.3 11 83.6 14.9 87 31.9 108.5 17.3…
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 (а) х %3D 503 feet (c) x = 321 feet (b) x = 645 feet (d) x = 726 feet 775 619 519 508 491 474 53 47 45 41 38 36 Find the regression equation. x+ (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)
For each of the following data sets: plot the data, determine the regression equation, and add the graph of the regression to the graph.
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 766 620 520 508 494 484 (a) x=501 feet (b) x=648 feet Stories, y 51 46 45 43 37 35 (c) x=310 feet (d) x=736 feet (1)Find the regression equation. y(^)=____ x+ (___) (2) Predict the value of y for x=501 (3) Predict the value of y for x=648 (4) Predict the value of y for x=310 (5) Predcit the value of y for x=736
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 feet

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a. Calculate the correlation coefficient r for the data above. b. Find the equation of the regression line for the data. c. Draw the regression line on the scatter plot for the data above.