solve correctly. I will rate accordingly. Passenger miles flown on Northeast Airlines, a commuter firm serving the Boston hub, are shown for the past 12 weeksWeekActual Passenger Miles (in thousands)1 23.457.89.101112151816191716181720181322a) Assuming an initial forecast for week 1 of 15,000 miles, use exponential smoothing to compute miles for weeks 2 through 12. Use a =0.22 (roundyour responses to two decimal places).Week1.59.10 11 12Forecasted Passenger Miles(in thousands)15.00 15.00 15.66 15.73 16.45 16.57 16.44 16.78 16.83 17.53

*Answer: FORECAST(T + 1) = FORECAST + (ALPHA * (ACTUAL DEMAND - FORECAST)) FORECAST 2 = 15 + (0.22…

Answered: Passenger miles flown on Northeast…

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 35EQ

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Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?
Cable TV The following table shows the number C. in millions, of basic subscribers to cable TV in the indicated year These data are from the Statistical Abstract of the United States. Year 1975 1980 1985 1990 1995 2000 C 9.8 17.5 35.4 50.5 60.6 60.6 a. Use regression to find a logistic model for these data. b. By what annual percentage would you expect the number of cable subscribers to grow in the absence of limiting factors? c. The estimated number of subscribers in 2005 was 65.3million. What light does this shed on the model you found in part a?
Special Rounding Instructions For this exercise set, round all regression parameters to three decimal places, but round all other answers to two decimal places unless otherwise indicated. First Down The following table shows the probability P, as a percentage, of a college football team converting on fourth down when not goal to go versus the distance D, in yards, to the first down maker. 28 D = distance, in yards P = probability 1 70 2 60 3 53 4 46 5 41 6 37 7 34 8 32 a.Use exponential regression to model the data. b.Plot the data along with the exponential model. c.What probability does the model give of gaining a first down for fourth down and 10yards to go? Note: the actual probability is 28.
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?
Sales of a video game released in the year 2000 took off at first, but then steadily slowed as time moved on. Table 4 shows the number of games sold, in thousands, from the years 20002010. a. Let x represent time in years starting with x=1 for the year 2000. Let y represent the number of games sold in thousands. Use logarithmic regression to fit a model to these data. b. If games continue to sell at this rate, how many games will sell in 2015? Round to the nearest thousand.

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