9 students were surveyed to see what their age is and what their income level is. Find the equation of the line using linear regression. Wewant to predict their age using their income.age182438221935281927income4567868358556452445871400975Just a side note, the 19 year old is making 1400, would be considered an outlier since they are making way more than everyone else.(y=-.0061x+34.9874 4 decimals)y=30.3709-.0064

Answered: Image /qna-images/answer/eb07430b-813f-4c0a-b902-337c0dc951c5.jpg

Answered: 9 students were surveyed to see what…

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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The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thousands of barrels per day) imported by a country, for the last seven years. Construct and interpret a 90% prediction interval for the amount of crude oil imported by the this country when the amount of crude oil produced by the country is 5,603 thousand barrels per day. The equation of the regression line is Oil produced,x Oil imported, y -1117x+ 15,844.101. 5,158 5,093 5,008 10,026 5,822 5.724 5,651 5,449 9,328 9,131 9,667 10,088 10,145 10,199 Construct and interpret a 90% prediction interval for the amount of crude oil imported when the amount of crude oil produced by the country is 5,603 thousand barrels per day Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) O A. There is a 90% chance that the predicted amount of oil imported is between thousand barreis, when there are…
please assist, the question states to "click on the datafile logo to reference the data" but the data is listed already in the question. when clicking that link, it opens up the same information in excel so please do not reject because the data is there already.
Isla Esme, Inc., sells tea products to various customers. In recent years, profits have been declining. The CFO of the business investigated the reasons for the profit decline and performed regression analysis for sales and costs. He determined that sales depend on product price, delivery speed, customer services, and marketing expenses. He also determined that total costs consist of variable costs of $25 per unit and fixed costs of $56,000. Marketing expenses have a coefficient of determination of 75% related sales.Question: Define the coefficient of determination and explain what it means in this scenario.
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The owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x 1) and newspaper advertising (x 2). The estimated regression equation was Weekly Gross Revenue ($1000s) Televison Advertising ($1000s) Newspaper Advertising ($1000s) 97 6 1.5 91 3 2 95 5 2.5 93 3.5 2.5 96 4 4.3 94 4.5 2.3 95 3.5 4.2 95 4 3.5 ŷ = 82.5 + 2.01 x 1 + 1.26 x 2The computer solution provided SST = 24 and SSR = 22.876. Compute R 2 and R a 2 (to 3 decimals). R 2 R a 2 When television advertising was the only independent variable, R 2 = 0.551 and R a 2 = 0.476. Are the multiple regression analysis results preferable?
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 98% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $878.The equation of the regression line is y=1.342x+55.816. Wages [state]- 712, 746, 786, 803, 841, 879, 918, 926, 954, 979 Wages [federal]- 1,024, 1,048, 1,098, 1,135, 1,195, 1,240, 1,270, 1,299, 1,340, 1,376 Construct and interpret a 98% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $878. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) PICK THE CORRECT ANSWER [A] We can be 98% confident that when the average weekly wages of state government employees is $878, the average weekly wages of…
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years, construct and interpret a 98% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $888 the equation of the regression line is y= 1.453x-47.386. Wages(state), X | 739|760|784|822|898|921|937|954|965| Wages (federal), Y |1,036|1,054|1,105|1,136|1,192|1,253|1,266|1,327|1,400|
2. The table below lists the annual land-line phone cost per costumer: Year 2012 2013 2014 2015 Cost ($) a. 692 610 Find a linear regression model for this data b. Interpret the slope of the model 580 C. Predict the annual land-line phone cost per customer in 2022 495 2016 434
A researcher knows that people with higher annual salaries commit fewer crimes. He is creating a regression model to predict the number of crimes a person will commit based on their salary Based on this information alone which of the following MUST be the slope of the regression line choose one 1.00 or 0.50 or -0.50
The slope of a regression line tells you how much or little a change in your dependent variable impacts your independent variable. O TrueO False
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
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