O Less than (or equal to) aThe p-value leads to a declslon to:O Accept HoO Reject HoO Do Not Reject HoThe conclusion isO 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 a significant negative linear correlation between advertising expense and profit.O There is insufficient evidence to make a conclusion about the linear correlation betweenadvertising expense and profit.Hint: Helpful Video on the Linear Regression Line [+]Helpful Video on CorrelationHelpful Video on Hypothesis Tests for Correlation [+)HintsQuestion Help: Message instructorSubmit Questionesc883F3FS%232$24.QWtabTYAScaps lockFshiftCVNcontroloptionB Listed below are paired data consisting of amounts spent on advertising (in millions of dollars) andthe profits (in millions of dollars}. Determine if there is a significant linear correlation betweenadvertising cost and profit. Use a significance level of 0.05 and round all values to 4 decimal places.Advertising Costt Profit271521303026Ho: p = 0Ha: p» 0Find the Linear Correlation CoefficientFind the p-valuep-value =The p-value isO Greater than aO Less than (or equal to) aThe p-value leads to a decision toO Accept HoO Reject HoDo Not Rejectiioesc888F1F3FSFBF9%2324&.12368QWRtabTYAScaps lockFHKCVNMcontroloptioncompBD

Oless than (or equal to) a The p-value leads to a decision to O Accept Ho O Reject Ho O Do Not Reject Ho The conclusion is 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 a significant negative linear correlation between advertising expense and profit. O There is insufficient evidence to make a conclusion about the linear correlation between advertising expense and profit.

Oless than (or equal to) a The p-value leads to a decision to O Accept Ho O Reject Ho O Do Not Reject Ho The conclusion is 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 a significant negative linear correlation between advertising expense and profit. O There is insufficient evidence to make a conclusion about the linear correlation between advertising expense and profit.

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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Annual high temperatures in a certain location have been tracked for several years. Let X represent the year and Y the high temperature. At the 0.05 significance level, does the data below show significant (linear) correlation between X and Y? x y 4 29.04 5 26.4 6 29.06 7 44.22 8 35.98 9 49.64 10 46.3 11 46.46 12 50.42 13 61.78 Yes, significant correlation No
Let x be the average number of employees in a group health insurance plan, and let y be the average administrative cost as a percentage of claims. x 3 7 15 32 75 y 40 35 30 26 18 (a) Make a scatter diagram of the data and visualize the line you think best fits the data. Flash Player version 10 or higher is required for this question. You can get Flash Player free from Adobe's website. (b) Would you say the correlation is low, moderate, or strong? positive or negative? strong and negative moderate and negative strong and positive low and negative low and positive moderate and positive (c) Use a calculator to verify that Σx = 132, Σx2 = 6932, Σy = 149, Σy2 = 4725, and Σxy = 2997. Compute r. (Round your answer to three decimal places.)r = As x increases, does the value of r imply that y should tend to increase or decrease? Explain. Given our value of r, we cannot draw any conclusions for the behavior of y as x increases. Given our value of r, y should tend to…
The data below was taken from the fat (g) and sodium (mg) found in different types of food found at fast food restaurants. 19 31 34 35 39 39 43 _y 920 1310 860 1180 940 1260 1500 a) Find the p-value to determine if there is a linear correlation between fat (g) and sodium (mg). Record the p-value below. Round to four decimal places. p-value = b) Is there a linear correlation between fat (g) and sodium (mg)? c) If there is a linear correation, write the correlation coefficient below. Otherwise, leave it blank. Round your final answer to four decimal places. d) If there is a linear correlation, write the regression equation below. Otherwise, leave it blank. Round all numbers to four decimal places. e) Using the data shown above, predict the the sodium found in fast food when the fat is 32 g. Round your final answer to two decimal places. f) If there is a linear correlation, what percentage of variation in sodium (mg) can be explained by fat (g)? If there is not a linear correlation, leave…
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3. .... 2. 5. 4. 3. 2. 参 dollars per year) Salary (thousands of Acreage dollars per year) Salary (thousands of square feet for the same houses, what would the correlation be? for some houses is 0.91. If you found the correlation between house price in thousands of dollars and area in 4.24 House Price The correlation between house price (in dollars) and area of the house (in square feet) Education (years) 2. 4. 0. 12 1. 8. 20. 60- Start Year 1985 40 2005 1995 2010 09 li. 06 (B) Full Bath 4. 1. 7. 6. 5. : (A) 0.777 0.374
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What is a reason why correlation does not imply causation? O Because correlations are not based on data. O Because you do not know if X or Y occurred first. O There could be a third variable that explains both X and Y. O Both b and c
2. A study was conducted to determine the relationship between a person’s monthly income in Omani Rials and the number of meals that person eats away from home per month. The data are shown below.
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After gathering data about the number of starfish and measuring the pollution in areas of the ocean you find a negative linear correlation between pollution levels and number of starfish. What can you conclude based on this information? a. There is a confounding variable that is affecting both pollution and starfish. b. As pollution rises the number of starfish falls c. That pollution is causing starfish to die, leading to the negative correlation d. That pollution is supporting starfish, leading to the negative correlation