42. Consider the random variable (X, Y) of Exercise 9.(a) Find the curve of regression of X on Y. Is the regression linear?(b) Find the mean value of X when y = .5.(c) Find the curve of regression of Y on X. Is the regression linear?(d) Find the mean value of Y when x = .75.

Detailed explanation:Regression Curves and Conditional Expectation:In statistics, regression…

Answered: 42. Consider the random variable (X, Y)…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

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Problem 1P

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A researcher is hired to investigate the relationship between the number of unauthorized days that employees are absent per year and the distance in miles between home and work for the employees. A sample of 10 employees was chosen and the results are listed in the chart below. Use the proper Data Analysis function in Excel to computethe regression equation needed to predict the number of missed days that could be expected foremployees who live certain distances away from the workplace. Distance to Work (miles): 1, 3, 4, 6, 9, 10, 12, 14, 14, 18 Number of Days Absent: 9, 6, 7, 7, 6, 4, 5, 3, 4, 2
A standardized exam's scores are normally distributed. In a recent year, the mean test score was 1482 and the standard deviation was 315. The test scores of four students selected at random are 1910, 1200, 2210, and 1390. Find the z-scores that correspond to each value and determine whether any of the values are unusual. The z-score for 1910 is (Round to two decimal places as needed.)
The least-squares regression equation is y = 743.3x+ 12,990 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7921. Complete parts (a) through (d). 55000- 20000- 15 20 25 30 35 40 45 50 55 60 Bachelor's % (a) Predict the median income of a region in which 20% of adults 25 years and older have at least a bachelor's degree. $ (Round to the nearest dollar as needed.) Median Income
What is the value of r2? Use the square root and your knowledge about the slope of the regression line to find the value of the correlation constant r. Based only on the value of r, do you think this line is useful for predicting life expectancy from the infant mortality rate? A new country called Arendelle has formed and has an infant mortality rate of 42 (deaths per 1000 live births). Use the equation of the regression line to predict the life expectancy for Arendelle. Round your answer to one decimal place. Another new country called Weselton has formed and has an infant mortality rate of 250 (deaths per 1000 live births). Recall some of the cautions we should take when considering correlation. In one or two complete sentences, explain why using the linear regression equation to make a life expectancy prediction is not a good idea for Weselton. If you had to choose exactly one potential influential outlier from the original data set, what would it be? Identify the point as an…
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day () and number of sit ups a person can do (y). The results of the regression were: y=ax+b a3D-0.838 b=28.783 es 72-0.784996 r=-0.886 rences borations Use this to predict the number of sit ups a person who watches 1 hours of TV can do, and please round your answer to a whole number. gle Drive ce 365 Submit Question adent Course aluations ere to search Chp ins prt sc delete f12 f9 f10 fa f5 f6 +1 f4 backspa & $4 8. 6 3 O E R T II 5
Select all the charts that violate the conditions for linear regression. These are residual plots so the red line represents the average residual, zero. 미 Od (a) (d) 매 Get help: Video (b) (e) (c) (1)
The profit of a company increased steadily over a ten-year span. The following ordered pairs show the number of units sold in hundreds and the profit in thousands of units over the ten-year span, (number of units sold, profit) for specific recorded years: (46,250), (48,305), (50,350), (52,390), (54,410) a) Use linear regression to determine a function y, where profit in thousands of dollars depends on the number of units sold in hundreds. b) Predict when the profit will exceed one million dollars.
Two variable are found to have a strong negative linear correlation. Pick the regression equation that best fits this scenario. y=0.82x−28 ˆy=0.32x−28 y= -0.82x+28 ˆy= -0.32x+28
The flow rate in a device used for air quality measurement depends on the pressure drop x (inches of water) across the device's filter. Suppose that for x values between 5 and 20, these two variables are related according to the simple linear regression model with true regression line y = -0.11 + 0.097x. (a.1) What is the true average flow rate for a pressure drop of 10 in.?(a.2) A drop of 15 in.?(b) What is the true average change in flow rate associated with a 1 inch increase in pressure drop?(c) What is the average change in flow rate when pressure drop decreases by 5 in.?
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13/
A trucking company considered a multiple regression model for relating the dependent variable y = total daily travel time for one of its drivers (hours) to the predictors x₁ = distance traveled (miles) and x₂ = the number of deliveries made. Suppose that the model equation is Y = -0.800+ 0.060x₁ +0.900x₂ + e (a) What is the mean value of travel time when distance traveled is 50 miles and four deliveries are made? hr (b) How would you interpret ₁ = 0.060, the coefficient of the predictor x₁? O When the number of deliveries is constant, the average change in travel time associated with a ten-mile (i.e. one unit) increase in distance traveled is 0.060 hours. O The total daily travel time increases by 0.060 hours when the distance traveled increases by 1. O When the number of deliveries is held fixed, the average change in travel time associated with a one-mile (i.e. one unit) increase in distance traveled is 0.060 hours. O The average change in travel time associated with a one-mile (i.e.…

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42. Consider the random variable (X, Y) of Exercise 9. (a) Find the curve of regression of X on Y. Is the regression linear? (b) Find the mean value of X when y = .5. (c) Find the curve of regression of Y on X. Is the regression linear? (d) Find the mean value of Y when x = .75.