An article gave a scatter plot, along with the least squares line, of x = rainfall volume (m³) and y = runoff volume (m³) for a particular location. The simple linear regression model provides a very good fit to data on rainfall and runoff volume (n=15) given below. Theequation of the least squares line is y=-1.082 +0.82861x, r² = 0.972, and s = 5.63.12 14 17 23 30 40 47 55 67 72 81 96 112 127y 5 10 14 14 15 26 26 46 37 47 52 70 83 100 100(a) Use the fact that s = 1.54 when rainfall volume is 40 m³ to predict runoff in a way that conveys information about reliability and precision. (Calculate a 95% PI. Round your answers to two decimal places.)m³Does the resulting interval suggest that precise information about the value of runoff for this future observation is available? Explain your reasoning.O Yes, precise information is available because the resulting interval is very wide.O Yes, precise information is available because the resulting interval is very narrow.O No, precise information is not available because the resulting interval is very wide.O No, precise information is not available because the resulting interval is very narrow.

The equation of the least squares regression line is .The data on x= rainfall volume and y=runoff…

Answered: An article gave a scatter plot, along…

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 certain town is located approximately 25 miles east of a large city. The data organized below include the appraised value (in thousands of dollars), land area of the property in acres, and age, in years, for a sample of 20 single-family homes located in the town. Develop a multiple linear regression model to predict appraised value based on land area of the property and age, in years. Complete part (a) a) State the multiple regression equation. Let X1i represent the land area of the property in acres and let X2i age, in years.
A wildlife biologist has spent the past 5 years studying the relationship between the length (inches) and the average weight (lb) of the striped bass. His results are summarized in the table below. Length (inches) 14 18 22 26 Weight (lb) 3 |11 14 Find the least squares regression line y = ax + b for the data in the table, where x represents the length of the fish in inches and y represents the weight in pounds. Use this regression line to estimate the average weight of a striped bass that is 21 inches in length. Oy=0.75(21) - 9.5 = 6.25 lb O y = 0.65(21) - 10.5 = 3.15 lb y = 0.95(21) - 10.5 = 9.45 lb y = 0.95(21)-8.5 = 11.45 lb y = 0.85(21) 12.5 = 5.35 lb
A least squares regression line was calculated to relate the length (cm) of newborn boys to their weight in kg. The line is weight=−5.82+0.1601 length. A newborn was 48 cm long and weighed 3 kg. According to the regression model, what was his residual? What does that say about him?
An article gave a scatter plot along with the least squares line of x = rainfall volume (m³) and y = runoff volume (m³) for a particular location. The accompanying values were read from the plot. x6 12 14 18 23 30 40 48 55 67 72 80 96 112 127 y 4 10 13 14 15 25 27 45 38 46 53 72 82 99 105 n USE SALT (a) Does a scatter plot of the data support the use of the simple linear regression model? O Yes, the scatterplot shows a reasonable linear relationship. O Yes, the scatterplot shows a random scattering with no pattern. O No, the scatterplot shows a reasonable linear relationship. O No, the scatterplot shows a random scattering with no pattern. (b) Calculate point estimates of the slope and intercept of the population regression line. (Round your answers to four decimal places.) slope intercept (c) Calculate a point estimate of the true average runoff volume when rainfall volume is 54. (Round your answer to four decimal places.) m3 (d) Calculate a point estimate of the standard deviation o.…
An engineer wants to determine how the weight of a gas-powered car, x, affects gas mileage, y. The accompanying data represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year. Complete parts (a) through (d) below. (a) Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. y=nothingx+(nothing) (Round the x coefficient to five decimal places as needed. Round the constant to one decimal place as needed.) (b) Interpret the slope and y-intercept, if appropriate. Choose the correct answer below and fill in any answer boxes in your choice. (Use the answer from part a to find this answer.) A. A weightless car will get nothing miles per gallon, on average. It is not appropriate to interpret the slope. B. For every pound added to the weight of the car, gas mileage in the city will decrease by nothing mile(s) per gallon, on…
Biologist Theodore Garland, Jr. studied the relationship between running speeds and morphology of 49 species of cursorial mammals (mammals adapted to or specialized for running). One of the relationships he investigated was maximal sprint speed in kilometers per hour and the ratio of metatarsal-to-femur length. A least-squares regression on the data he collected produces the equation ŷ = 37.67 + 33.18x where x is metatarsal-to-femur ratio and y is predicted maximal sprint speed in kilometers per hour. The standard error of the intercept is 5.69 and the standard error of the slope is 7.94. Construct a 96% confidence interval for the slope of the population regression line. Give your answers precise to at least two decimal places. contact us help 6:42 PM povecy polcy terms of use careers A E O 4») 18 -క90.4 58 12/14/2020 a 17 |耳即 delets prt sc insert 112 19 18 + 16 backspace f5 fA
estion 7 of 15 Suppose the manager of a gas station monitors how many bags of ice he sells daily along with recording the highest temperature each day during the summer. The data are plotted with temperature, in degrees Fahrenheit (°F), as the explanatory variable and the number of ice bags sold on as the response variable. The least squares regression (LSR) line for the data is y = -114.05 +2.17x. On one of the observed days, the temperature was 82 °F and 66 bags of ice were sold. Determine the number of bags of ice predicted to be sold by the LSR line, ŷ, when the temperature is 82 °F. Enter your answer as a whole number, rounding if necessary. ice bags Using the predicted value you just found, compute the residual at this temperature. residual = ice bags DOLL
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…
Independent variable data is listed in cells B2 through B100, and dependent variable data is in cells C2 through C100. Which spreadsheet function would calculate the slope of a linear regression model of this data? Group of answer choices =SLOPE(B2:B100,C2:C100) =SLOPE(C2:C100,B2:B100) =SLOPE(B2,C2) =SLOPE(C2,C100,B2,B100)
An article gave a scatter plot along with the least squares line of x = rainfall volume (m³) and y = runoff volume (m³) for a particular location. The accompanying values were read from the plot. X 4 12 14 20 23 30 40 50 55 67 72 83 96 112 127 y 4 10 13 14 15 25 27 45 38 46 53 75 82 99 104 USE SALT (a) Does a scatter plot of the data support the use of the simple linear regression model? o Yes, the scatterplot shows a reasonable linear relationship. Yes, the scatterplot shows a random scattering with no pattern. No, the scatterplot shows a reasonable linear relationship. No, the scatterplot shows a random scattering with no pattern. (b) Calculate point estimates of the slope and intercept of the population regression line. (Round your answers to four decimal places.) slope X X .84210 intercept -1.86631 (c) Calculate a point estimate of the true average runoff volume when rainfall volume is 45. (Round your answer to four decimal places.) 40.2387 X m 3 (d) Calculate a point estimate of…
Use the least squares regression model to estimate the maximum sustained wind speed in a hurricane when the pressure reading is 950 mb. Interpret the slope of the least squares regression model in the context of wind speed and atmospheric pressure. Determine the coefficient of determination and interpret its meaning in the context of wind speed and atmospheric pressure.
Report the equation of the regression line and interpret it in the context of the problem

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