Caselet #2 STEEL SPECIMENS tis thought that abrasion loss in certain steel specimens should be a linear function of the Rockwell hardness measure. A sample of eight specimens gave the following results: Rockwell Hardness 60 62 63 67 70 74 79 81 Abrasion Loss 251 245 246 233 221 202 188 170 Conduct a Correlation and Regression Analysis given a 95% confidence level.

Caselet #2 STEEL SPECIMENS tis thought that abrasion loss in certain steel specimens should be a linear function of the Rockwell hardness measure. A sample of eight specimens gave the following results: Rockwell Hardness 60 62 63 67 70 74 79 81 Abrasion Loss 251 245 246 233 221 202 188 170 Conduct a Correlation and Regression Analysis given a 95% confidence level.

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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The accompanying table lists overhead widths (cm) of seals measured from photographs and the weights (kg) of the seals. Find the (a) explained variation, (b) unexplained variation, and (c) prediction interval for an overhead width of 8.9 cm using a 99% confidence level. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. Click the icon to view the seal data. a. The explained variation is (Round to the nearest integer as needed.) b. The unexplained variation is. (Round to the nearest integer as needed.) c. The 99% prediction interval for an overhead width of 8.9 cm is kg
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Listed below are paired data consisting of amounts spent on advertising (in millions of dollars) and the profits (in millions of dollars). Determine if there is a significant linear correlation between advertising cost and profit . Use a significance level of 0.05 and round all values to 4 decimal places. Advertising Cost Profit 3 19 4 16 24 6 29 7 25 27 10 30 Ho: p = 0 На: р * 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is O Less than (or equal to) a O Greater than a The p-value leads to a decision to O Do Not Reject Ho O Accept Ho O Reject Ho The conclusion is O There is a significant negative linear correlation between advertising expense and profit. O There is a significant linear correlation between advertising expense and profit. O There is a significant positive linear correlation between advertising expense and profit. O There is insufficient evidence to make a conclusion about the linear correlation between advertising expense and…
e) Perform the F Test making sure to state the null and alternative hypothesis.
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6
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Can you please check my work