Might we be able to predict life expectancies from birthrates?Below are bivariate data giving birthrate and life expectancy information for each of twelve countries. For each of the countries, both x, the number of births perone thousand people in the population, and y, the female life expectancy (in years), are given. Also shown are the scatter plot for the data and the least-squaresregression line. The equation for this line is y = 81.92-0.47x.Birthrate, xFemale life expectancy, y(in years)(number of births per 1000 people)34.365.742.564.513.371.3xx19.172.345.060.032.962.514.775.950.458.449.753.324.274.349.761.327.873.5Send data to calculator VSend data to ExcelBased on the sample data and the regression line, answer the following.(a) From the regression equation, what is the predicted female life expectancy (in years) when the birthrate is 45.0births per 1000 people? Round your answer to one or more decimal places.0(b) What was the observed female life expectancy (in years) when the birthrate was 45.0 births per 1000 people?Female life expectancy(In years)xx30 35 40 45 50 55 6010Birthrate(number of births per 1000 people)?

The regression equation is, Y^ = 81.92-0.47*X Here given that, The value of x is 45 then we've to…

Answered: Might we be able to predict life…

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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A study of king penguins looked for a relationship between how deep the penguins dive to seek food and how long they stay underwater. For all but the shallowest dives, there is a linear relationship that is different for different penguins. The study report gives a scatterplot for one penguin titled " The relation of dive duration (DD) to depth (D)." Duration DD is measured in minutes and depth D is in meters. The report then says, " The regression equation for this bird is: DD = 2.3 + 0.0021 D. %3D (a) What is the slope of the regression line?. ANSWER minutes per meter. (b) According to the regression line, how long does a typical dive to a depth of 400 meters last? ANSWER minutes.
Please provide a detailed explanation for the questions attached.
Please answer parts d, e and f.
Might we be able to predict life expectancies from birthrates? Below are bivariate data giving birthrate and life expectancy information for each of twelve countries. For each of the countries, both x, the number of births per one thousand people in the population, and y, the female life expectancy (in years), are given. Also shown are the scatter plot for the data and the least-squares regression line. The equation for this line is y=82.25 -0.48x. ^ Birthrate, x (number of births per 1000 people) 35.5 44.9 29.7 19.9 13.7 27.0 51.9 15.0 50.9 49.7 39.6 24.4 Send data to calculator Send data to Excel Female life expectancy, y (in years) 67.9 57.9 61.7 71.4 72.5 73.5 55.4 76.5 58.2 60.6 64.4 74.4 Based on the sample data and the regression line, complete the following. Female life expectancy (in years) 85 80+ 75+ 70- 65+ 60- 55+ 50 x X x ++ 10 15 20 25 (b) According to the regression equation, for an increase of one (birth per 1000 people) in birthrate, there is a corresponding decrease…
You make the bold assumption that there is a linear relationship between number of ads and sales revenues. Find the intercept, b0, and the slope, b1, of the estimated regression equation that will minimize the sum of square residuals.
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…
Dr. Lillian Fok, a New Orleans psychologist, specializes in treating patients who are agoraphobic (i.e., afraid to leave their homes). The following table indicates how many patients Dr. Fok has seen each year for the past 10 years. It also indicates what the robbery rate was in New Orleans during the same year. Year Number of Patients Robbery Rate per 1,000 Population The simple linear regression equation that shows the best relationship between the number of patients and the robbery rate is (round your responses to three decimal places) where y Number of Patients and x = Robbery Rate. = 1 2 3 4 6 7 36 33 40 41 55 60 58.3 61.1 73.4 75.7 81.1 89.0 101.1 5 40 8 54 94.8 9 58 103.3 10 61 116.2
Consumers are often interested in the fuel efficiency of the vehicles they choose to buy, so much so that they will research the various models they consider buying. Fuel efficiency can depend on a variety of variables. In this analysis, there are 73 automobiles that are popular with consumers. A regression analysis has been performed; the dependent variable is CityMPG (EPA miles per gallon in city driving), and independent variables are Length (vehicle length in inches), Width (vehicle width in inches), Weight (vehicle weight in pounds), and ManTran (1 if manual shift transmission, 0 otherwise). The level of significance is 0.05. Use the following MegaStat output to answer questions about this regression analysis. a. State the regression equation. b. How would CityMPG be affected if the width of a vehicle increased by an inch? c. Estimate the CityMPG for a vehicle with a length of 190 inches, a width of 75 inches, a weight of 4100 pounds, and a manual. Round your answer to the nearest…
Might we be able to predict life expectancies from birthrates? Below are bivariate data giving birthrate and life expectancy information for each of twelve countries. For each of the countries, both x, the number of births per one thousand people in the population, and y, the female life expectancy (in years), are given. Also shown are the scatter plot for the data and the least-squares regression line. The equation for this line is y = 82.17 -0.47x. Birthrate, x (number of births per 1000 people) 14.3 27.4 51.1 46.8 24.9 29.9 18.2 41.6 49.4 14.1 33.9 49.3 Send data to calculator Female life expectancy, y (in years) 75.6 70.5 58.2 59.0 73.3 62.7 73.6 65.2 62.4 74.3 67.0 53.9 Send data to Excel Female life expectancy (In years) Based on the sample data and the regression line, answer the following. 85+ 80+ 75+ 70+ 65 60 55+ 50 (a) From the regression equation, what is the predicted female life expectancy (in years) when the birthrate is 29.9 births per 1000 people? Round your answer to…
A study of king penguins looked for a relationship between how deep the penguins dive to seek food and how long they stay underwater. For all but the shallowest dives, there is a linear relationship that is different for different penguins. The study report gives a scatterplot for one penguin titled " The relation of dive duration (DD) to depth (D)." Duration DD is measured in minutes and depth D is in meters. The report then says, " The regression equation for this bird is: DD = 2.02 + 0.0081 D. (a) What is the slope of the regression line?. ANSWER minutes per meter. (b) According to the regression line, how long does a typical dive to a depth of 400 meters last? ANSWER minutes. Speak
The U.S. Postal Service is attempting to reduce the number of complaints made by the public against its workers. To facilitate this task, a staff analyst for the service regresses the number of complaints lodged against an employee last year on the hourly wage of the employee for the year. The analyst ran a simple linear regression in SPSS. The results are shown below. The current minimum wage is $5.15. If an employee earns the minimum wage, how many complaints can that employee expect to receive? Is the regression coefficient statistically significant? How can you tell?
For major league baseball teams, do higher player payrolls mean more gate money? Here are data for each of the American League teams in the year 2002. The variable x denotes the player payroll (in millions of dollars) for the year 2002, and the variable y denotes the mean attendance (in thousands of fans) for the 81 home games that year. The data are plotted in the scatter plot below, as is the least-squares regression line. The equation for this line is y = 11.43 + 0.23x. Player payroll, x (in Mean attendance, y (in $1,000,000s) thousands) Anaheim 62.8 28.52 Baltimore 56.5 33.09 40- Boston 110.2 32.72 35 Chicago White Sox 54.5 20.74 30- Cleveland 74.9 32.35 25- Detroit 54.4 18.52 Kansas City 49.4 16.30 15- Minnesota 41.3 23.70 10+ New York Yankees 133.4 42.84 Oakland 41.9 26.79 20 40 60 80 100 120 140 Seattle 86.1 43.70 Player payroll, Тarmpa Bay 34.7 13.21 X (in $1,000,000s) Техas 106.9 29.01 Toronto 66.8 20.25 Send data to calculator Send data to Excel Based on the sample data and…

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