Use the model found above to answer this question. Using the revenue data for Jesaki Inc. for the past few years, we apply linear regression to the data to find a model y = 33.9 x– 814, where r is Jesaki's annual revenue in billions of US dollars, and t is the number of years since 2000. Use this model, together with the revenue model you found for Walmart to answer the question below. When will Jesaki's revenue overtake Walmart? Note: I am asking for the year, not the number of years since 2000. This may happen between two years. Round to the nearest year.
Use the model found above to answer this question. Using the revenue data for Jesaki Inc. for the past few years, we apply linear regression to the data to find a model y = 33.9 x– 814, where r is Jesaki's annual revenue in billions of US dollars, and t is the number of years since 2000. Use this model, together with the revenue model you found for Walmart to answer the question below. When will Jesaki's revenue overtake Walmart? Note: I am asking for the year, not the number of years since 2000. This may happen between two years. Round to the nearest year.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
7 please answer this
Transcribed Image Text:Use the model found above to answer this question.
Using the revenue data for Jesaki Inc. for the past few years, we apply linear regression to the data
to find a model
y = 33.9 x- 814,
where r is Jesaki's annual revenue in billions of US dollars, and t is the number of years since
2000. Use this model, together with the revenue model you found for Walmart to answer the
question below.
When will Jesaki's revenue overtake Walmart?
Note: I am asking for the year, not the number of years since 2000. This may happen between two
years. Round to the nearest year.
Transcribed Image Text:Walmart Annual
Year
Revenue
(Billions of US dollars)
2021
559.151
2020
523.964
2019
514.405
2018
500.343
2017
485.873
2016
482.130
2015
485.651
2014
476.294
2013
468.651
2012
446.509
2011
421.849
2010
408.085
2009
404.254
2008
377.023
2007
348.368
2006
312.101
2005
284.310
Apply linear regression to the data in the table to find a model
y = mx + b,
where y is Walmart's annual revenue in billions of US dollars, and x is the number of years since
2000.
Use the model y
= mx + b with m rounded to the nearest tenth and b rounded to the nearest
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