The table lists weights (pounds) and highway mileage amounts (mpg) for sevenautomobiles. Use the sample data to construct a scatterplot. Use the first variable forthe x-axis. Based on the scatterplot, what do you conclude about a linear correlation?Weight (lb)Highway (mpg)Which scatterplot below shows the data?A.40-20-200050002795 3225 3470323428Weight (lb)B.40-20+2000D5000Weight (lb)4085 4155 2225252338C.●20+2000●●●●5000Weight (lb)Is there a linear relationship between weight and highway mileage?A. No, there appears to be no relationship.B. Yes, as the weight increases the highway mileage decreases.C. No, there appears to be a relationship, but it is not linear.D. Yes, as the weight increases the highway mileage increases.40-20-20003440295000Weight (lb)

Data given Weight (lb):2795,3225,3470,4085,4155,2225,3440 Highway(mpg):34,32,28,25,23,38,29

Answered: The table lists weights (pounds) and…

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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EQuestion Help The ages (in years) of 10 men and their systolic blood pressures (in millimeters of mercury) are shown in the attached data table with a sample correlation coefficient r of 0.899. Remove the data entry for the man who is 50 years old and has a systolic blood pressure of 200 millimeters of mercury from the data set and find the new correlation coefficient. Describe how this affects the correlation coefficient r. Use technology E Click the icon to view the data set. The new correlation coefficient r gets stronger, going from 0.899 to (Round to three decimal places as needed.) Data Table Age, x Systolic blood pressure, y 16 109 26 121 38 141 46 131 50 200 65 182 69 198 More 32 129 56 175 Enter your answer in the answer box 119 23
Determine whether the data described are qualitative or quantitative. Styles of shoes. OQualitative O Quantitative Continue esc 12
Use the computing formula to calculate the coefficient of correlation for the vending machine data below. YEAR Maıntanence cost($) (y) 4 148 2 128 3 133 5 154 2 118 3 145 4 143 5 159 4 142 3 127
I w 6 9 1 12 X 2 3 5 7 10 11 12 15 16 y 62 67 65 86 80 85 88 84 92 ▸ Determine the correlation coefficient for this set of data and define the strength and direction of the correlation.
Based on the data below, answer the following question: Draw a scatter diagram that highlights the relationship between Local Tuition and Students per Faculty. Find out the correlation coefficient between Local Tuition and Students per Faculty. (Keep 2 decimal places.) Business School Full-Time Enrollment Students per Faculty Local Tuition ($) Foreign Tuitiion ($) English Test Work Experience Starting Salary ($) 1 Melbourne Business School 200 5 24,420 29,600 No Yes 71,400 2 University of New South Wales (Sydney) 228 4 19,993 32,582 No Yes 65,200 3 Indian Institute of Management (Ahmedabad) 392 5 4,300 4,300 No No 7,100 4 Chinese University of Hong Kong 90 5 11,140 11,140 No No 31,000 5 International University of Japan (Niigata) 126 4 33,060 33,060 Yes No 87,000 6 Asian Institute of Management (Manila) 389 5 7,562 9,000 No Yes 22,800 7 Indian Institute of Management (Bangalore) 380 5 3,935 16,000 No No 7,500 8 National University of Singapore 147 6 6,146 7,170…
Using the scatter plot of the registered nurse salary data shown, what type of correlation, if any do you think the data have? Explain. Registered Nurses 70 O A. There appears to be a strong positive linear correlation. As the years of experience of the registered nurses increase, salaries tend to decrease. 65 60 O B. There appears to be a strong positive linear correlation. As the years of experience of the registered nurses increase, salaries tend to increase. 55 50 OC. There appears to be a strong negative linear correlation. As the years of experience of the registered nurses increase, salaries tend to decrease. 45 40 O D. There does not appear to be any linear correlation. 2 46 8 10 12 14 16 18 20 22 24 Years of experience O Time Remaining: MacBook Air 80 esc F9 F10 F1 F2 F3 F4 F5 F6 F7 F8 23 $ & 1 7 Annual salary (in thousands) * CO
One of the biggest factors in determining the value of a home is the square footage. The accompanying data represent the square footage and selling price (in thousands of dollars) for a random sample of homes for sale in a certain region. Complete parts (a) through (h) below. A Click the icon to view the housing data. (c) Determine the linear correlation coefficient between square footage and asking price. Question Help v (Round to three decimal places as needed.) (d) Is there a linear relation between square footage and asking price? O Yes No (e) Find the least-squares regression line treating square footage as explanatory variable. (Round the slope to three decimal places as needed. Round the intercept to one decimal place as needed.) (f) Interpret the slope. Select the correct choice below and, if necessary, fill in the answer box to complete your choice O A. For everv additional thousand dollars in sellina orice the sauare footade increases bvi Click to select your answer(s).…
The following graph plots data for tax per gallon and internal miles.Carefully explain what the graph is about, and what it captures. What are the limitations of the correlation and what can a researcher do toovercome these?
ASSESSMENT Direction: Read, analyze and answer the following problems below. Show all necessary solutions. 1. The data below show the age and systolic blood pressure of six randomly selected subjects. Compute for the correlation coefficient and interpret the results. Age (x) Pressure (y) 43 48 56 61 67 70 128 120 135 143 141 152
The graph below is a scatter plot between liabilities and assets, bothexpressed in millions. i. Critically assess this scatter plot explaining about the relationship betweentwo variables.ii. A researcher claims that the correlation is showing that changes in assetscause changes in liabilities. Is he right or wrong? Explain your answer.
Use a graphing calculator to find the equation of the line of best fit for the data in the table below. Find the value of the correlation coefficient r. Then predict the number of movie tickets sold in 2014.
Weight (lbs.) 173 184 194 214 168 220 188 188 207 167 217 Systolic Blood Pressure 132 143 153 162 154 168 137 149 159 128 1 1. The sample correlation coefficient is _____________

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