5. The figure shows a scatterplot with a regression line for teachers' average pay and the expenditure perpupil for each state for public schooling in 2007, according to The 2009 World Almanac and Book of Facts.(a) From the graph, is the correlation between teachers' average pay and the expenditure per pupilpositive or negative?(b) Interpret the slope.(c) Interpret the intercept or explain why it should not be interpreted.Ilomework - 3Predicted Expenditure = -1424 + 0.2315 (Average Pay)17500 -1500012500100007500500035000 40000 45000 50000 55000 60000 65000Average PayExpenditure per Pupil

Given : Let X : Average Pay Y : Expenditure per Pupil From this graph ; fitted regression line…

Answered: 5. The figure shows a scatterplot with…

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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7. The table below shows the round-trip fare for flights from one city on major airlines. These were the lowest prices found online in early 2010. The airlines varied, but the travel dates were all the same. Determine the linear regression for the cost of a round-trip ticket given the distance traveled, use your regression to estimate the cost of a 1500-mi flight, and state the correlation coefficient, r, and describe the trend, shape, and strength for the data contained in this problem. Distance (mi.) Cost ($) 205 183 968 180 3097 598 1939 277 1976 313 1033 318 2977 448 1752 408 1143 335
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A manager of a local retail store analyzes the relationship between the number of rainy days and sales by reviewing the store’s data for the previous six months. She computes the correlation between sales and number of rainy days as -0.90. Select ALL that apply. a. There is a strong positive linear relationship between sales and number of rainy days. b. As the number of rainy days increases sales decrease. c. As the number of rainy days increases sales increase. d. There is a strong negative linear relationship between sales and the number of rainy days.
ologist was recording various temperatures (in degrees Celsius) and predicting the amount of glucose produced by a plant (in milligrams). Suppose the linear equation was the following: ?̂ = 12.7 − 0.223? Suppose the correlation coefficient was −0.12. How would you classify the correlation between temperature and amount of glucose?
We expect a car’s highway gas mileage to be related to its city gas mileage (in mpg). Data for all 1209 vehicles in the government’s 2016 Fuel Economy Guide gives the regression line highway mpg=7.903+(0.993×city mpg) for predicting highway mileage from city mileage. (a) What is the slope of this line? (Give your answer to 33 decimal places.) slope = Say in words what the numerical value of the slope tells you. Select the best option from these choices: A) On average, highway mileage increases by 0.993 mpg0.993 mpg for each additional mpg in city mileage. B) Highway gas mileage increases with city gas mileage by 7.903 mpg7.903 mpg for each additional mpg in city mileage. C) On average, highway mileage decreases by 0.993 mpg0.993 mpg for each additional mpg in city mileage. D) For every 7.903 mpg in city gas mileage, highway gas mileage increases about 0.993 mpg. E) On average, highway mileage increases by 7.903 mpg for each additional mpg in city mileage.…
What type of correlation is exhibited by the following graph? Independent Variable a. Positive Correlation b. No Correlation c. Negative Correlation d. Either positive or negative correlation Dependent Variable
A regression modrel examining the amount of distance a long-ddistance runner runs (in miles) to predict the amount of fluid the runner drinks (ounces0 has a slope of 4.6. Which interpretation is appropiate? The correlation is needed to interpret this value. Arunner drinks minimum of 4.6 oz. We predict 4.6 miles for every ounce that drunk. We predict for every mile run, the runner drinks 4.6 more ounces. Each mile adds 4.6 more ounces.
The owner of Showtime Movie Theatres Inc. would like to predict weekly gross revenue as a function of advertising expenditures. Use 0.05 level of significance.Historical data for a sample of eight weeks follow: Weekly Gross Renvenue Telelvision Newspaper Adveritising ($1000s) Adveritising a) Develop an estimated regression equation to predict weekly gross revenue as a function of advertising expenditures. ($1000s) ($1000s) 96 5.0 1.5 90 20 2.0 b) Explain in simg when 1000s are spent on television and newspaper then the revenue will in 95 4.0 1.5 92 2.5 2.5 c) Predict weekly 95 3.0 3,3 94 3.5 2.3 d) What is the R2 value? 0.9190 94 2.5 4.2 94 3.0 2.5 e) What is the Hypothesis Test? Use the t test to determine the significance of each independent variable. State the t test, p-values, and your conclusion. g) What is the cor Reject Ho SUMMARY OUTPUT pression Statstica Mutiple R 0.958663444 0.9190356 R Square 0.88664984 Adusted R Square Standard Eror 0.642587303 Obervations ANOVA Syaicance…
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Bloomberg Intelligence listed 50 companies to watch in 2018 (bloomberg.com/features/companies-to-watch-2018). Twelve of the companies are listed here with their total assets and 12-month sales. Let sales be the dependent variable and total assets the independent variable. Draw a scatter plot Compute the correlation coefficient Determine the regression equation For a company with $100 billion in assets, predict the 12- month sales.
use the sample data to construct a scatterplot. Use the first variable for the x-axis. Based on the scatterplot, what do you conclude about a linear correlation? FORECAST AND ACTUAL TEMPERATURES The table lists actual high temperatures and the high temperatures that were previously forecasted for these same days. The table includes data for ten different days near the author’s home. What does the result suggest about the accuracy of five-day predicted high temperatures?
lecture(11.12): A large amount of scatter in a scatter plot is an indication that the relationship between the two variables is (a) negative (b) strong (c) weak (d) moderate (e) positive

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