Let Y represent the profit (or loss) for a certain company X years after 1960. Based on the datashown below, a statistician calculates a linear model Y = 0.81X19.44.Xy =12345678910111213141516y19.8517.5216.1916.7614.4314.912.6713.4412.8111.9810.759.027.797.868.236.8Use the model to estimate the profit in 1975

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Answered: Let Y represent the profit (or loss)…

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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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 professor in the School of Business in a university polled a dozen colleagues about the number of professional meetings they attended in the past five years (x) and the number of papers they submitted to refereed journals (y) during the same period. The summary data are provided. Fit a simple linear regression model between x and y by finding out the estimates of intercept and slope. Comment on whether attending more professional meetings would result in publishing more papers. n n n = 12, x = 4, y = 12, X₁Y₁ = 320 i=1 x² = 234, i=1 The estimated regression line is y = 36.4 + (-6.10 )x. (Round to two decimal places as needed.) Comment on whether attending more professional meetings would result in publishing more papers. Let it be unclear that attending more professional meetings affects the number of published papers if the value used to make that determination is between 1 and 1. Because the of the regression equation is it would appear that attending more professional meetings ▼
The following table compares the length of a rhinoceros horn (in inc Use linear regression to find the equation for the line that best fits decimal places. Write your final answer in a form of an equation y = 37 199 203 34 49 46 245 226 40 43 52 55 259 X. 187 230 268
Suppose trips/wk =3.1 -0.15(dist) is a linear model that predicts the number of supermarket trips a family makes per week when they live a certain distance (in miles) from a supermarket. It was established by sampling people who live within 10 miles of a supermarket. Which of the following is the correct interpretation of the slope? O a. For each additional trip that the family makes, they live 0.15 miles away from the store O b. For each additional mile away from the store the family lives, they make 0.15 more visits per week O. For each additional mile away from the store the family lives, they make 0.15 fewer visits per week O d. For each additional trip they make to the store, they live an additional 3.1 miles away. O e. For each additional mile away they live, they make 3.1 more trips to the stor.
The table lists the cost in millions of dollars for a 30-second commercial for selected years. Year 1994 1998 2004 2008 2011 Cost 33.7 34.2 35.0 35.5 35.9 a. Find a linear function f that models the data. b. Estimate the cost in 2010 and compare the estimate to the actual value of $36.6 million. Did your estimate involve interpolation or extrapolation? a. Use linear regression to determine the equation of the line that best fits the data. The linear function is f(x) = (Type an expression using x as the variable. Use integers or decimals for any numbers in the expression. Round to three decimal places as needed.)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 Price/Book Value Ratio Return on Equity 13.032 1.405 8.305 2.113 6.654 1.239 3.262 2.449 5.291 2.398 7.719 0.353 2.569 7.593 5.104 2.012 4.797 2.182 4.129 1.918 1.549 1.951 5.046 2.417 2.159 3.011 1.725 5.582 4.698 Growth% 6.385 11.846 135.669 12.459 0.073 25.092 14.188 8.804 22.766 38.082 18.985 25.696 24.519 19.666 11.624 22.849 49.965 69.649 36.696 3.819 41.139 9.218 29.108 17.772 25.114 29.295 23.764 31.405 9.497 14.759 18.541 12.026 39.016 14.228 39.439 14.097 27.022 14.841 13.237 20.669 17.311 14.887 15.849 5.601 16.775 11.172 8.401 16.161 18.404 23.973 16.673 14.725 46.605 28.839 52.021
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An ice cream truck owner collects data on the number of sales made each day and the average temperature that day. He computes a regression line for predicting the number of sales based on how far the daily temperature is from freezing (0 degrees Celsius) and finds sales = 3.22 - 1.8 (degrees over 0 Celsius). Identify the "y-intercept". A. -1.8 B. 1.8 C. 3.22 D. 0

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Let Y represent the profit (or loss) for a certain company X years after 1960. Based on the data shown below, a statistician calculates a linear model Y = 0.81X + 19.44.