The following table lists the birth weights (in pounds), x, and the lengths (in inches), y, for a set of newborn babies at a local hospital.Birth Weight(in Pounds), xAnswerLength (inInches), yBirth Weights and Lengths10 721 187 4 12 7 10 3 11712 1216 21 19 22 15 21 20Copy DataStep 2 of 2: Predict the length of an 8-pound baby. Assume the regression equation is appropriate for prediction. Round your answer to two decimal placesnecessary.TablesKeyboard S

Birth weight (in pounds) x Length (in inches) y 10 21 7 18 7 17 4 16 12 21 7 19 10 22…

Answered: The following table lists the birth…

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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Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross f its budget is $100 million. Use a significance level of a= 0.05. Budget ($)in Millions 45 17 114 67 70 49 117 67 3 62 128 21 11 152 10 Gross (5) in Millions 114 12 103 72 131 121 105 105 51 95 203 24 13 289 46 Click the icon to view the critical values of the Pearson correlation coefficient r. The regression equation is y= . (Round to one decimal place as needed.)
Write out the regression equation based on the output.
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 775 619 519 508 (a) x= 501 feet (c) x=318 feet 491 474 (b) x = 651 feet (d) x= 729 feet 53 47 45 43 38 37 Find the regression equation. (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)
The personnel director of a large hospital is interested in determining the relationship (if any) between an employee’s age and the number of sick days the employee takes per year. The director randomly selects ten employees and records their age and the number of sick days which they took in the previous year. Employee 1 2 3 4 5 6 7 8 9 10 Age 30 50 40 55 30 28 60 25 30 45 Sick Days 7 4 3 2 9 10 0 8 5 2 Copy Data The estimated regression line and the standard error are given. Sick Days=14.310162−0.2369(Age) se=1.682207se=1.682207 Find the 95% confidence interval for the average number of sick days an employee will take per year, given the employee is 26. Round your answer to two decimal places.
Please assist with question b
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.
Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sq ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract of the output obtained: The regression equation is Price = B + ¢Bedroom + yHouse Size + ALot Size Predictor Coef SE Coef т P 37718 14177 2.66 ** Constant Bedrooms 2306 6994 0.33 0.742 House Size 74.3 52.98 0.164 Lot Size -4.36 17.02 -0.26 0.798 S= 25023 R-Sq=56.0% R-Sq (adj) =54.6% Source DF SS MS F P Regression 3 76501718347 25500572782 *** **** Residual 96 60109046053 626135896 Error Total 99 a) Write out the regression equation. b) Fill in the missing values *, ** *** and ****
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
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…
Draw the weights and heights scatter diagram of your data by using EXCEL and give your interpretation. Find the equation of the regression line from the following data

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