Question 44) ListenThe MAPE of the linear regression method is2.47%6.78%9.17%2.63%1 Year234567891011121314A151617182002200320042005200620072008200920102011201220132014201520162017BSales45474848525356585964697073767980>n3D

MAPE is the measure of absolute percentage error. It is calculated by subtracting the actual and…

Answered: Question 4 Listen The MAPE of the…

Algebra & Trigonometry with Analytic Geometry

13th Edition

ISBN:9781133382119

Author:Swokowski

Publisher:Swokowski

Chapter5: Inverse, Exponential, And Logarithmic Functions

Section5.3: The Natural Exponential Function

Problem 42E

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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?
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.
Cellular Phone Subscribers The table shows the numbers of cellular phone subscribers y in millions in the United States from 2008 through 2013. Source: CTIA- The Wireless Association Year200820092010201120122013Number,y270286296316326336 (a) Find the least squares regression line for the data. Let x represent the year, with x=8 corresponding to 2008. (b) Use the linear regression capabilities of a graphing utility to find a linear model for the data. How does this model compare with the model obtained in part a? (c) Use the linear model to create a table of estimated values for y. Compare the estimated values with the actual data.
Question 16 Regression analysis was applied between sales (in $1000s) and advertising (in $100s), and the following regression function was obtained. = 500 + 4x Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is _____. $505,000 $900 $40,500 $900,000
2.state each of the ﬁve assumptions of the classical regression model (OLS) and give an intuitive explanation of the meaning and need for each of them
If the general linear regression model is given by the equation: y = a + b?; considering the informationobtained in Figure 2 above, compute the value of a.
Question 5 - what is the y-intercept of the equation of the regression line y = 36.11695 + 7.20508x A. 7.20508 B. 36.11695 C. Y D. X Question 6 - what is the slop of the equation of the regression line y = 36.11695 + 7.20508x? A. 7.20508 B. 36.11695 C . Y D . X

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Question 4 Listen The MAPE of the linear regression method is 2.47% 6.78% 9.17% 2.63% 1 Year 2 3 4 5 6 7 8 A 9 10 11 12 13 14 15 16 17 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 B Sales 45 47 48 48 52 53 56 58 59 64 69 70 73 76 79 80 C