Use the data below for the PHONES questions that follow.Data compiled from the CIA World Factbook, https://www.cia.gov/.The number of cell phones in use in a country can be approximated from thenumber of main lines in use in that country by using the regression equationyhat=25+3x which had an R² of about 90%.(The numbers here are millions. For example, "1.2" would represent 1.2 million or1,200,000.)PHONES 1At the time the data was collected, the USA had about 314 million cell phones in use and about 150million main lines in use. What was the residual for the USA? Enter a number of millions. For example, ifyour answer is 2.85 million enter "2.85". Do not enter anything else such as symbols or words.

Answered: Image /qna-images/answer/da181675-565d-48cb-b500-cd86601f1dd7.jpg

Answered: Use the data below for the PHONES…

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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what % of the variation is ( height, or head circumference) explained by the least-squares regression model. (Round to one decimal place as needed.)
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Refer to the Baseball 2018 data, which reports information on the 2018 Major League Baseball season. Let attendance be the dependent variable and total team salary be the independent variable. Determine the regression equation and answer the following questions. Click here for the Excel Data Filea-1. Draw a scatter diagram.1. On the graph below, use the point tool to plot the point corresponding to the Attendance and its team salary (Salary 1).2. Repeat the process for the remainder of the sample Salary 2, Salary 3, … ).3. To enter exact coordinates, double-click on the point and enter the exact coordinates of x and y. a-2. From the diagram, does there seem to be a direct relationship between the two variables?multiple choice 1 Yes No b. What is the expected attendance for a team with a salary of $100.0 million? (Round your answer to 4 decimal places.) c. If the owners pay an additional $30 million, how many more people could they expect to attend? (Round your answer to 3…
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Listed below are foot lengths (mm) and heights (mm) of males. Find the regression equation, letting foot length be the predictor (x) variable. Find the best predicted height of a male with a foot length of 272.7 mm. How does the result compare to the actual height of 1776 mm? Foot Length 282.3 277.8 252.8 258.7 279.0 258.4 274.1 261.7 Height 1785.0 1771.0 1675.7 1645.7 1859.3 1710.2 1789.2 1737.0 The regression equation is ŷ = + (x. (Round the y-intercept to the nearest integer as needed. Round the slope to two decimal places as needed.) The best predicted height of a male with a foot length of 272.7 mm is (Round to the nearest integer as needed.) How does the result compare to the actual height of 1776 mm? O A. The result is close to the actual height of 1776 mm. O B. The result is exactly the same as the actual height of 1776 mm. O C. The result is very different from the actual height of 1776 mm. O D. The result does not make sense given the context of the data. C mm.
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Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as y = – 65.95x + 49.28 and the r = - 0.993. What proportion of the variation in y can be explained by the variation in the values of x? r2 = Report answer as a percentage accurate to one decimal place.
A. Develop an estimated regression equation that can be used to predict the price of the stock based on the number of shares of company's stocks sold and the volume of exchange. B. Interpret the coefficients of the estimated regression equation that you found in Part a. C. If in a given day, the number of shares of the company that were sold was 94,500 and the volume of exchange on the New York Stock Exchange was 16 million, what would you expect the price of the stock to be?

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