Homework Help is Here – Start Your Trial Now!
Math
Statistics
(c) Compute the leverage values for these data. (Round your answers to two decimal places.) Leverage Value 22 10 0.38 24 19 0.28 26 29 0.22 28 33 0.20 40 68 0.92 ✓ ✓ Do there appear to be any influential observations in these data? Explain. Because the leverage value for [no observations ✔ is greater than 1 x, we conclude that there are no influential observations ✔

(c) Compute the leverage values for these data. (Round your answers to two decimal places.) Leverage Value 22 10 0.38 24 19 0.28 26 29 0.22 28 33 0.20 40 68 0.92 ✓ ✓ Do there appear to be any influential observations in these data? Explain. Because the leverage value for [no observations ✔ is greater than 1 x, we conclude that there are no influential observations ✔

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
See similar textbooks
icon
Related questions
Question

I tried 2, 1 and 0.92 they are all wrong. 

Part c the incorrect one. Need help with that.

Data for two variables, x and y, follow. Xi Yi 10 19 29 33 68 (a) Develop the estimated regression equation for these data. (Round your numerical values to two decimal places.) ŷ = -55.28+3.11x (b) Compute the studentized deleted residuals for these data. (Round your answers to two decimal places.) Xi Yi 24 22 10 22 24 26 28 40 Studentized 40 68 Deleted Residual 19 -0.12 -1.94 26 29 1.79 28 33 0.40 Xi Yi -1.90 At the 0.05 level of significance, can any of these observations be classified as an outlier? Explain. (Select all that apply.) Observation x; = 22 can be classified as an outlier since it has a large studentized deleted residual (greater than to.025 or less than -to.025). Observation x; = 24 can be classified as an outlier since it has a large studentized deleted residual (greater than to.025 or less than -to.025). Observation X; = 26 can be classified as an outlier since it has a large studentized deleted residual (greater than to.025 or less than -to.025). Observation X; = 28 can be classified as an outlier since it has a large studentized deleted residual (greater than to.025 or less than -to.025). Observation | X₁ ¡= 40 can be classified as an outlier since it has a large studentized deleted residual (greater than to.025 or less than -t0.025). None of the observations can be classified as outliers since they do not have large studentized deleted residuals (greater than to.025 or less than to.025). (c) Compute the leverage values for these data. (Round your answers to two decimal places.) Leverage Value 22 10 0.38 24 19 0.28 26 29 0.22 28 33 0.20 40 68 0.92 Do there appear to be any influential observations in these data? Explain. Because the leverage value for no observations ✔ is greater than 1 x, we conclude that there are no influential observations
Transcribed Image Text:Data for two variables, x and y, follow. Xi Yi 10 19 29 33 68 (a) Develop the estimated regression equation for these data. (Round your numerical values to two decimal places.) ŷ = -55.28+3.11x (b) Compute the studentized deleted residuals for these data. (Round your answers to two decimal places.) Xi Yi 24 22 10 22 24 26 28 40 Studentized 40 68 Deleted Residual 19 -0.12 -1.94 26 29 1.79 28 33 0.40 Xi Yi -1.90 At the 0.05 level of significance, can any of these observations be classified as an outlier? Explain. (Select all that apply.) Observation x; = 22 can be classified as an outlier since it has a large studentized deleted residual (greater than to.025 or less than -to.025). Observation x; = 24 can be classified as an outlier since it has a large studentized deleted residual (greater than to.025 or less than -to.025). Observation X; = 26 can be classified as an outlier since it has a large studentized deleted residual (greater than to.025 or less than -to.025). Observation X; = 28 can be classified as an outlier since it has a large studentized deleted residual (greater than to.025 or less than -to.025). Observation | X₁ ¡= 40 can be classified as an outlier since it has a large studentized deleted residual (greater than to.025 or less than -t0.025). None of the observations can be classified as outliers since they do not have large studentized deleted residuals (greater than to.025 or less than to.025). (c) Compute the leverage values for these data. (Round your answers to two decimal places.) Leverage Value 22 10 0.38 24 19 0.28 26 29 0.22 28 33 0.20 40 68 0.92 Do there appear to be any influential observations in these data? Explain. Because the leverage value for no observations ✔ is greater than 1 x, we conclude that there are no influential observations
Expert Solution
trending now

Trending now

This is a popular solution!

steps

Step by step

Solved in 3 steps with 4 images

SEE SOLUTIONCheck out a sample Q&A here
Blurred answer
Recommended textbooks for you
MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman
SEE MORE TEXTBOOKS