This exercise requires the use of a statistical software package. The cotton aphid poses a threat to cotton crops. The accompanying data on y = Infestation rate (aphids/100 leaves) x1 = Mean temperature (°C) x2 = Mean relative humidity appeared in an article on the subject. y x1 x2 y x1 x2 62 21.0 57.0 76 24.8 48.0 86 28.3 41.5 94 26.0 56.0 99 27.5 58.0 99 27.1 31.0 105 26.8 36.5 119 29.0 41.0 101 28.3 40.0 75 34.0 25.0 64 30.5 34.0 44 28.3 13.0 28 30.8 37.0 18 31.0 19.0 15 33.6 20.0 22 31.8 17.0 31 31.3 21.0 24 33.5 18.5 68 33.0 24.5 41 34.5 16.0 5 34.3 6.0 22 34.3 26.0 19 33.0 21.0 24 26.5 26.0 43 32.0 28.0 55 27.3 24.5 59 27.8 39.0 60 25.8 29.0 81 25.0 41.0 88 18.5 53.5 76 26.0 51.0 103 19.0 48.0 109 18.0 70.0 96 16.3 79.5 Find the estimated regression equation of the multiple regression model y = ? + ?1x1 + ?2x2 + e. (Round your numerical values to two decimal places.) = Assess the utility of the multiple regression model using a significance level of 0.05. Calculate the test statistic. (Round your answer to two decimal places.) F = Use technology to calculate the P-value. (Round your answer to four decimal places.) P-value = What can you conclude? Reject H0. We have convincing evidence that the multiple regression model is useful.Fail to reject H0. We do not have convincing evidence that the multiple regression model is useful. Fail to reject H0. We have convincing evidence that the multiple regression model is useful.Reject H0. We do not have convincing evidence that the multiple regression model is useful.

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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Question

This exercise requires the use of a statistical software package.

The cotton aphid poses a threat to cotton crops. The accompanying data on

y	=	Infestation rate (aphids/100 leaves)
x₁	=	Mean temperature (°C)
x₂	=	Mean relative humidity

appeared in an article on the subject.

y	x₁	x₂	y	x₁	x₂
62	21.0	57.0	76	24.8	48.0
86	28.3	41.5	94	26.0	56.0
99	27.5	58.0	99	27.1	31.0
105	26.8	36.5	119	29.0	41.0
101	28.3	40.0	75	34.0	25.0
64	30.5	34.0	44	28.3	13.0
28	30.8	37.0	18	31.0	19.0
15	33.6	20.0	22	31.8	17.0
31	31.3	21.0	24	33.5	18.5
68	33.0	24.5	41	34.5	16.0
5	34.3	6.0	22	34.3	26.0
19	33.0	21.0	24	26.5	26.0
43	32.0	28.0	55	27.3	24.5
59	27.8	39.0	60	25.8	29.0
81	25.0	41.0	88	18.5	53.5
76	26.0	51.0	103	19.0	48.0
109	18.0	70.0	96	16.3	79.5

Find the estimated regression equation of the multiple regression model

y = ? + ?₁x₁ + ?₂x₂ + e.

(Round your numerical values to two decimal places.)

Assess the utility of the multiple regression model using a significance level of 0.05.

Calculate the test statistic. (Round your answer to two decimal places.)

F =

Use technology to calculate the P-value. (Round your answer to four decimal places.)

P-value =

What can you conclude?

Reject H₀. We have convincing evidence that the multiple regression model is useful.Fail to reject H₀. We do not have convincing evidence that the multiple regression model is useful. Fail to reject H₀. We have convincing evidence that the multiple regression model is useful.Reject H₀. We do not have convincing evidence that the multiple regression model is useful.

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