Consider the following regression:Salary, = 478807.0504 + 735832.7839Experience, + 11921192.95Japanese -635832.7839Expreience x Japanese;%3DA Japanese position player with 0 years of experience would be predicted to earnon average.---

The predicted value of Y is equal linear function of X. The regression equation helps to predict the…

Consider the following regression: Salary, 478807.0504 + 735832.7839Experience, +11921192.95Japanese – 635832.7839Erpreience x Japanese, %3D A Japanese position player with O years of experience would be predicted to earn on average. --

Consider the following regression: Salary, 478807.0504 + 735832.7839Experience, +11921192.95Japanese – 635832.7839Erpreience x Japanese, %3D A Japanese position player with O years of experience would be predicted to earn on average. --

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Would the regression in Equation be useful for predicting test scoresin a school district in Massachusetts? Why or why not?
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A regression was run to determine if there is a relationship between hours of TV watched per day (x) and the number of sit-ups a person can do (y). The results were: y = a+bx b = -0.89 a = 23.49 r² = 0.6519 r = -0.8074 a. If a person watches 7 hours of television a day, predict how many sit-ups he can do. b. If a person can do 4 sit ups, predict how many hours of television a day they watch. hours
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QUESTION: A wholesaler supplies products to 10 retail stores, each of which will independently make an order on a given day with chance 0.35. What is the probability of getting exactly 2 orders? Find the most probable number of orders per day and the probability of this number of orders. Find the expected number of orders per day.
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