OThe following table gives the advertising revenue of Google. Revenue Year (Billion $) 2008 21.1 2010 28.4 2012 43.7 2014 59.6 2016 79.4 2018 116.3 a) Create a scatterplot for (t, R) where t is the number of years since 2008 and R is the revenue in billions of dollars. b) Draw a linear model through the points (2, 28.4) and (8, 79.4). Write the equation of the linear model that passes through these points. Show how you get your equation. 3) c) If the trend of the linear model continues, in what year would you predict the revenue to reach $150 billion? d) Find the relative change in Google's profit from 2008-2018. Explain the meaning of your answer. 1072 0+10 Jin)=

OThe following table gives the advertising revenue of Google. Revenue Year (Billion $) 2008 21.1 2010 28.4 2012 43.7 2014 59.6 2016 79.4 2018 116.3 a) Create a scatterplot for (t, R) where t is the number of years since 2008 and R is the revenue in billions of dollars. b) Draw a linear model through the points (2, 28.4) and (8, 79.4). Write the equation of the linear model that passes through these points. Show how you get your equation. 3) c) If the trend of the linear model continues, in what year would you predict the revenue to reach $150 billion? d) Find the relative change in Google's profit from 2008-2018. Explain the meaning of your answer. 1072 0+10 Jin)=

Name: Answer a, b,c OThe following table gives the advertising revenue of Go
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Description: Answer a, b,c OThe following table gives the advertising revenue of Google.RevenueYear(Billion $)200821.1201028.4201243.7201459.6201679.42018116.3a) Create a scatterplot for (t, R) where t is the number of years since 2008 and R is the revenue in bil

Elementary Linear Algebra (MindTap Course List)

8th Edition

ISBN:9781305658004

Author:Ron Larson

Publisher:Ron Larson

Chapter2: Matrices

Section2.CR: Review Exercises

Problem 90CR

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Use a software program or a graphing utility to write v as a linear combination of u1, u2, u3, u4, u5 and u6. Then verify your solution. v=(10,30,13,14,7,27) u1=(1,2,3,4,1,2) u2=(1,2,1,1,2,1) u3=(0,2,1,2,1,1) u4=(1,0,3,4,1,2) u5=(1,2,1,1,2,3) u6=(3,2,1,2,3,0)
Redo Exercise 5, assuming that the house blend contains 300 grams of Colombian beans, 50 grams of Kenyan beans, and 150 grams of French roast beans and the gourmet blend contains 100 grams of Colombian beans, 350 grams of Kenyan beans, and 50 grams of French roast beans. This time the merchant has on hand 30 kilograms of Colombian beans, 15 kilograms of Kenyan beans, and 15 kilograms of French roast beans. Suppose one bag of the house blend produces a profit of $0.50, one bag of the special blend produces a profit of $1.50, and one bag of the gourmet blend produces a profit of $2.00. How many bags of each type should the merchant prepare if he wants to use up all of the beans and maximize his profit? What is the maximum profit?
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.
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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