The grades of a class of 9 students on a midterm report (x) and on the final examination (y) are shown below. Use the data to complete parts (a) and (b).X 77 5081 67y71 72 83 9479 36 48 849699 99 6899 67 D(a) Estimate the linear regression line.ŷ=+x(Round the constant to one decimal place as needed. Round the coefficient to three decimal places as needed.)

From the provided information, x y 77 81 50 67 71 79 72 36 83 48 94 84 96 99 99…

Answered: The grades of a class of 9 students on…

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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Use the Regression tool on the accompanying wedding data, using the wedding cost as the dependent variable and attendance as the independent variable. Complete parts a through c. Click the icon to view the wedding data. X a. What is the regression model? Wedding Cost = +(xAttendance (Round to three decimal places as needed.) Wedding Attendance and Cost Wedding Cost 62700 Attendance 300 54000 350 48000 150 40000 200 36000 250 32000 150 31000 250 29500 300 27000 250 27000 200 26000 150 25000 200 23000 200 22000 200 22000 200 21000 200 20000 100 19000 150 19000 200 18000 150 17000 100 16000 100 13000 150 8000 50 5000 50 Wedding Cost Attendance
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.)
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
A researcher is interested in seeing if there is a relationship the amount of time in minutes a person spends in their car during the day and the number of minutes that person spends listening to music. Car Time 63 14 241 93 140 3 91 45 22 Music Time 73 16 260 142 206 31 78 47 29 a. Find the equation of the regression line and use it to make a prediction of the dollars purchased by someone who visits the website 4 times.b. Interpret the slope in the context of the problem.c. Interpret the y-intercept in the context of the problem or state why it is not applicable.d. State the null and alternative hypotheses for the hypothesis test of correlation e. Find the pvalue and state your conclusion in the context of the study.
The file Galton on D2L contains the 928 observations Francis Galton used in 1885 to estimate the relationship between the heights of parents and the heights of their children. The column Children refers to the height (in inches) of a child, and the column Mid-Parents refers to the average height (in inches) of the mother and father of that child. You can download this file into Excel and Minitab. a. Calculate the regression Height of Children = a +b (Height of Mid-Parents). b. Calculate the average for Height of Children, and calculate the average Height of Mid-Parents. c. Create a new variable in Minitab which is the Height of Children measured in terms of deviations from its mean. Call this new variable y. Also, create a new variable in Minitab with is the Height of Mid-Parents measured in terms of deviations from its mean. Call this new variable x. Calculate the regression y = a + bx. You can create the new y and x variables in Excel of Minitab, whichever you find more convenient.…
b. Find the equation of the regression line for the minutes the actor appeared shirtless in a film and the film's opening weekend gross. y = ___x + ____(Round to two decimal places as needed)
Find the slope (b1) for the regression equation for the following values. Round to 3 decimal places. Define Variables xi yi 33 180 25 170 50 200 65 201 57 160 27 165
Use the data given below to answer a -c. Heigh (IN) 71 70.5 71 72 70 66.5 70 71 Weight (lb) 125 119 128 128 119 127 123 105 Find the regression equation letting the first variable (height) to be the independent variable (x). Find the best-predicted weight for a person whose height is 69in. What percentage of the variation in weight can be explained by the linear relationship between height and weight.
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…
The following table shows the reported net sales by Nokia in 2008, 2009, and 2010. Year 2008 2009 2010x 0 1 2Sales ($ millions) 20 50 60 Find the Equation of the Linear Regression Line. Rounds decimal values to the nearest tenths.
Show your work please.
Use the scatterplot of Vehicle Registrations below to answer the questions Vehicle Registrations in the United States, 1925- 2011 Vehicles millions 300 y = 3.0161x - 5819.5 R? = 0.9695 250 200 150 100 50 1920 -50 1940 1960 1980 2000 2020 Year Write a sentence explaining the value of the slope for this regression line. For every increase in year, the number of vehicle registrations in the US increases by 3.0161 million. For every increase in year, the number of vehicle registrations in the US increases by 5819.5. For every increase in vehicle registrations in the US, the number of years increases by 5819.5. For every increase in vehicle registrations in the US, the number of years increases by 3.0161 million. Registrations (in millions)

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