) The table shows the population of a certain city for selected years between 1950 and 2003.Years after 1950 | Population12,42120143,112290,0893040375,297445, 052471,1265055By using your calculator to find the logistic regression equation that best fits the data, determinethe limiting size of the population.A) 494,194B) 482,550C) 478,550D) 499,107

Given information: The data represents the values of the variables x = Year and y = Population.

Answered: The table shows the population of a…

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter7: Distance And Approximation

Section7.3: Least Squares Approximation

Problem 33EQ

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Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
Which of the following are feasible equations of a least squares regression line for the annual population change of a small country from the year 2000 to the year 2015? Select all that apply.
Use the technique of linear regression to find the line of best fit for the given points. Round any intermediate calculations to no less than six decimal places, and round the coefficients to two decimal places. (1,9), (2,6), (3,4), (4,10), (5,3), (6,2), (7,3)

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The table shows the population of a certain city for selected years between 1950 and 2003. Years after 1950 | Population 12,421 20 143,112 30 290,089 40 375,297 50 445, 052 55 471,126 By 1using vour calculator to find the logistic rogroscion oguation that host fits the data dotor