homeworks 1-4Linear Regression Examples1. The table below shows the number of people, p, and suitcases, s, on 8 airplanesрSa) Find the regression equation.v or(2.) The table below shows the population, in thousands, during certain years since 2000.69121511.9 12.5 13.2 13.663 115 153 192 224 297 331 375112 209 278379 500 586 712302year0population 10.7noia) Find the regression equation.yearsalaryYourMANa) Find the regression equation.haslection5,824$16,9203. The table below shows the salary, in millions, made by the highest paid major league baseball playerduring certain years.311.1a) Find the regression equation.47112b) Predict the number of suitcases on an airplanewith 500 people.b) Predict the population in 2025.sw o bas19825,824$10,3001985 1991 1993 1996 1998 20012.1 3.8 6.2 9.3 14.9 22lead to en nl edt brittuod64. The table below shows the mileage, m, on six cars that were recently traded in, along with theirvalue, v.tikwa2130 of 1990 Won •azoorioblbom (a10 BMJ48b) Predict the salary of the highest paid player in2020.73,00558,126$5,300$7,225| 21105,092 159,062$3,125$1,800SM3TATS (Hbv-*133nickelsBALLb) Predict the value of a car with 13,258 miles.otetody thingTofauna)2007214--All TL! - AL

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Answered: The table below shows the number of…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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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)
Tuition($) Applicant Pool Applicant 950 76210 11040 1225 78000 10940 1325 67420 8670 1350 70380 9040 1500 62580 7410 1675 59260 7080 1800 57930 6350 1975 60130 6110 a. Using POMQM, develop the multiple regression equation for these data. b. What is the coefficient of determination for this regression equation? c. Determine the forecast for freshman applicants for a tuition rate of $1700 per semester, with a pool of applicants of 63000.
A cafe company wants to determine how the money they spend on Google ads impacts their monthly revenue. Over 6 consecutive months, they vary the amount they spend on their Ads (in $) and record the associated revenue (in $) for each month. The data is shown below: l Revenue 50 427 75 472 100 467 125 529 150 518 175 543 A) Develop a regression equation for predicting monthly revenue based on the amount spent with Ads. What is the y-intercept? B) What is the sample correlation between these two variables? C) What is the slope of your regression equation? Give your answer to two decimal places. D) Using a 0.05 level of significance, does this regression equation appear to have any value for predicting revenue based on Ads?
Predict the average lifespan of an animal in years when the incubation/gestation time is 12 months. Animal: Nile crocodile, Aldabra giant tortoise, Lake sturgeon,Galápagos tortoise, Bowhead whale Average Lifespan (in Years):100 152 152 177 211 Incubation/ Gestation (in Months)3 8 0.25 4.7 regression equation and regression line if needed
The number of initial public offerings of stock issued in a 10-year period and the total proceeds these offerings (in millions) are shown in the table. The equation of the regression line is y = 43.977x+ 19,528.57. Complete parts a and b. 379 55 18,716 29,004 42,559 30,325 67,231 65,155 21,100 12,473 31,455 27,712 Issues, x 424 457 695 500 499 74 180 158 Proceeds. (a) Find the coefficient of determination and interpret the result. (Round three decimal places as needed.)
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Find the value of regression
Using data from 50 workers, a researcher estimates Wage Be + B₁Education + B2Experience + B3Age +, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. A portion of the regression results is shown in the following table. Coefficients Standard Error t Stat p-Value Intercept 7.45 3.79 1.97 0.0554 Education 1.06 0.37 2.86 0.0063 Experience 0.37 0.18 2.06 0.0455 Age -0.02 0.06 -0.33 0.7404 a-1. Interpret the point estimate for ẞ1. As Education increases by 1 year, Wage is predicted to increase by 1.06/hour. As Education increases by 1 year, Wage is predicted to increase by 0.37/hour. As Education increases by 1 year, Wage is predicted to increase by 1.06/hour, holding Age and Experience constant. As Education increases by 1 year, Wage is predicted to increase by 0.37/hour, holding Age and Experience constant. a-2. Interpret the point estimate for ẞ2. ○ As Experience…
Find (u, v), |u, vl, and d(u, v) for the given inner product defined on R". u = (-5, 4), v = (0,-2), (u, v) 3u,v, + UZV2 (a) (u, v) (b) (c) (d) (A 'n)p
A physician wishes to know whether there is a relationship between a father’s weight (in pounds) and his new born sons’ weight (in pounds). The data are given here Fathers Weight 176 145 187 210 196 142 205 215 152 145 Sons Weight 6.6 8.2 9.2 7.1 8.8 9.3 7.1 8.6 7.8 6.0 Develop the regression equation for the sample Predict the sons weight based on the father’s weight of 300, 250 and 400.
The median household incomes in South Carolina from 2013 and 2017 are listed in the table below. (Source: “South Carolina Household Income.” Department of Numbers, https://www.deptofnumbers.com/income/south-carolina/) Year 2013 2014 2015 2016 2017 Median Household Income $46,548 $46,887 $48,876 $50,566 $50,570 Determine the linear regression model, I(t), where t = years since 2013 and I = Median Household Income. A. I(t) = 1172.3t + 46548 B. I(t) = 1172.3t + 46345 C. I(t) = 1172.3t D. I(t) = 1172.3t - 2E+06
Tuition($) Applicant Pool Applicant 950 76210 11040 1225 78000 10940 1325 67420 8670 1350 70380 9040 1500 62580 7410 1675 59260 7080 1800 57930 6350 1975 60130 6110 a. Using POMQM, develop the multiple regression equation for these data. b. What is the coefficient of determination for this regression equation? c. Determine the forecast for freshman applicants for a tuition rate of $1700 per semester, with a pool of applicants of 63000. CAN YOU SHOW ME ALL THE ANSWER WİTH EXCELL TABLE

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