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.1 Calculate the value of the test statistic. 1.2 Reject H0 if t≤  - or if t≥ - . (please fill in dash) 1.3 Give the correct decision and conclusion. Do not reject H0 and conclude that there is no linear association. Do not reject H0 and conclude that there is a linear association. Reject H0 and conclude that there is a linear association. Reject H0 and conclude that there is no linear association. 1.4  Give the percentage of variation in the weight of the snakes (Y)(Y) that is explained by the length of the snakes (X)(X). 1.5 Calculate the estimated weight (in g) of a snake that is 54cm long. 1.6  Which one of the following describes the relationship between XX and YY. For every increase of 1g in the weight, the length increases with 0.9444cm. For every increase of 1g in the weight, the length increases with 10.507cm. For every increase of 1cm in the length, the weight increases with 10.507g. For every increase of 1cm in the length, the weight increases with 0.9444g. For every increase of 1g in the weight, the length increases with 9.444cm. For every increase of 1cm in the length, the weight increases with 9.444g.

.1 Calculate the value of the test statistic. 1.2 Reject H0 if t≤  - or if t≥ - . (please fill in dash) 1.3 Give the correct decision and conclusion. Do not reject H0 and conclude that there is no linear association. Do not reject H0 and conclude that there is a linear association. Reject H0 and conclude that there is a linear association. Reject H0 and conclude that there is no linear association. 1.4  Give the percentage of variation in the weight of the snakes (Y)(Y) that is explained by the length of the snakes (X)(X). 1.5 Calculate the estimated weight (in g) of a snake that is 54cm long. 1.6  Which one of the following describes the relationship between XX and YY. For every increase of 1g in the weight, the length increases with 0.9444cm. For every increase of 1g in the weight, the length increases with 10.507cm. For every increase of 1cm in the length, the weight increases with 10.507g. For every increase of 1cm in the length, the weight increases with 0.9444g. For every increase of 1g in the weight, the length increases with 9.444cm. For every increase of 1cm in the length, the weight increases with 9.444g.

MATLAB: An Introduction with Applications
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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1.1 Calculate the value of the test statistic.

1.2 Reject H0 if t≤  - or if t≥ - . (please fill in dash)

1.3 Give the correct decision and conclusion.

  • Do not reject H0 and conclude that there is no linear association.
  • Do not reject H0 and conclude that there is a linear association.
  • Reject H0 and conclude that there is a linear association.
  • Reject H0 and conclude that there is no linear association.

1.4  Give the percentage of variation in the weight of the snakes (Y)(Y) that is explained by the length of the snakes (X)(X).

1.5 Calculate the estimated weight (in g) of a snake that is 54cm long.

1.6 

Which one of the following describes the relationship between XX and YY.

  • For every increase of 1g in the weight, the length increases with 0.9444cm.
  • For every increase of 1g in the weight, the length increases with 10.507cm.
  • For every increase of 1cm in the length, the weight increases with 10.507g.
  • For every increase of 1cm in the length, the weight increases with 0.9444g.
  • For every increase of 1g in the weight, the length increases with 9.444cm.
  • For every increase of 1cm in the length, the weight increases with 9.444g.
In a population of snakes, researchers caught and measured ten adult females. Their body lengths (X) and weights (Y) are shown in the table below. Length (in cm) 54 55 50 69 56 66 56 68 53 61 Weight (in g) 373 352 316 568 420 473 402 482 355 427 The hypothesis to be tested is Ho :p = 0 H1 :p + 0 at a = 0.1 level of significance where pis the population correlation coefficient. Given: The estimated simple linear regression equation is Ỹ = -201 + 10.507X. The sample correlation coefficient is r = 0.9444.
Transcribed Image Text:In a population of snakes, researchers caught and measured ten adult females. Their body lengths (X) and weights (Y) are shown in the table below. Length (in cm) 54 55 50 69 56 66 56 68 53 61 Weight (in g) 373 352 316 568 420 473 402 482 355 427 The hypothesis to be tested is Ho :p = 0 H1 :p + 0 at a = 0.1 level of significance where pis the population correlation coefficient. Given: The estimated simple linear regression equation is Ỹ = -201 + 10.507X. The sample correlation coefficient is r = 0.9444.
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