A research company summarized the average time spent everyday by teenagers watching television.Year19992000 2001 2002 2003 2004 2005 2006Time (min) 1791951961901871851821692The above data can be modelled by a quadratic regression function in the form: y = ax² +bx+c, wherex is the time in minutes and y is the year from 1999.a) Determine the regression equation. Round decimals to one decimal place, if necessary.y=ax³ + bx + Cequation = 5.8x4x + 2050.7a = 5.8C = 2050.7b=-47b) In which year does the maximum amount of television occur?Year 4.(2002)c) To the nearest minute, how much time spent watching television occurs is 2008?

Since, it is not mentioned which problem to be solved, we'll be answering the first question only.…

Answered: a) Determine the regression e Y= ax +…

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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The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.
Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
bThe average rate of change of the linear function f(x)=3x+5 between any two points is ________.
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?

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a) Determine the regression e Y= ax + bx + C