3:20 PM Wed Feb 15Oil and Gas Prices The average gasoline price per gallon (in cities) and the cost of a barrel of oil are shown for a randomselection of weeks from 2009-2010. Is there a linear relationship between the variables?Oil (S)'60.33 87.09 78.12 82.91 64.76 69.58Gasoline ($) 2.188 2.350 2.625 2.627 2.489 2.791Send data to ExcelPart: 0 / 5Part 1 of 5(a) Draw the scatter plot for the variables.Next Part4.5....www-awu.connectmath.com4.3.5+Oil and Gas Prices1XS*47%Submit Assignmen2023 McGraw Hill LLC. All Rights Reserved. Terms of Use | Privacy Ce

We have given data set, Oil (x) Gasoline y 60.33 2.188 87.09 2.35 78.12 2.625 82.91…

Answered: Oil and Gas Prices The average gasoline…

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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NHL Assists and Total Points A random sample of scoring leaders from the National Hockey League (NHL) showed the following numbers of assists and total points. Based on these data, can it be concluded that there is a significant relationship between the two? Draw the scatter plots for the variables. Assists 59 68 44 65 67 69 Total points 109 101 95 94 91 89
A scatterplot of two variables is a picture of the relationship represented in a correlation. Group of answer choices True False
The table lists weights (pounds) and highway mileage amounts (mpg) for seven automobiles. 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? Weight (lb) Highway (mpg) Which scatterplot below shows the data? A. 40- 20- 2000 5000 2795 3225 3470 32 34 28 Weight (lb) B. 40- 20+ 2000 D 5000 Weight (lb) 4085 4155 2225 25 23 38 C. ● 20+ 2000 ● ● ● ● 5000 Weight (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- 2000 3440 29 5000 Weight (lb)
Would it be OK to use the line to predict the age of the wife if the husband is 80 years old? Explain your answer.
At Bats and Hits The data below show the number of three-base hits (triples) and the number of home runs hit during the season by a random sample of MLB teams. Is there a significant relationship between the data? Triples 25 24 34 31 19 29 Home runs 312 236 301 279 276 270 Send data to Excel Part 1 of 5 Your Answer is correct (a) Draw the scatter plot for the variables. At Bats and Hits Home runs y 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340 360 380 x 5 10 15 20 25 30 35 40 45 50 55 60 0 Triples Part: 1 / 5 1 of 5 Parts Complete Part 2 of 5 (b) Compute the value of the correlation coefficient. Round your answer to at least three decimal places. r=?
The ordered pairs below give the winning times (in seconds) of a 100-meter freestyle swim race at a regularly-held competition from 1984 through 2012. (1984, 54.22) (2000, 52.13) (1988, 53.23) (2004, 52.14) (1992, 52.94) (2008, 51.42) (1996, 52.80) (2012, 51.30) (a) Sketch a scatter plot of the data. Let y represent the winning time (in seconds) and let t = 84 represent 1984. (b) Sketch the line that you think best approximates the data and find an equation of the line. (Round the slope and y-intercept to one decimal place.) y = (c) Use the regression feature of a graphing utility to find the equation of the least squares regression line that fits the data. (Round the slope and y-intercept to two decimal places.) y =
Which graph shows the line of best fit for the data?
The ordered pairs below give the winning times (in seconds) of a 100-meter freestyle swim race at a regularly-held competition from 1984 through 2012. (1984, 55.12) (2000, 53.03) (1988, 54.13) (2004, 53.04) (1992, 53.84) (2008, 52.32) (1996, 53.70) (2012, 52.20) (a) Sketch a scatter plot of the data. Let y represent the winning time (in seconds) and let t = 84 represent 1984. (b) Sketch the line that you think best approximates the data and find an equation of the line. (Round the slope and y-intercept to one decimal place.) y = (c) Use the regression feature of a graphing utility to find the equation of the least squares regression line that fits the data. (Round the slope and y-intercept to two decimal places.) y = (d) Compare the linear model you found in part (b) with the linear model you found in part (c). The models are not similar.The models are similar.
Correlation and linear regression
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Make box and whisker plot of average temperature of California in June, December, and march. Also, compare22 the results. year March (°C) June (°C) December (°C) 2004 7 22 -10 2005 8 23 -69 2006 10 24 -10 2007 9 23 -8 2008 8 25 -7 2009 10 26 -9 2010 27 -6 2011 11 29 -5 2012 16 29 -10 2013 17 29 -10 2014 13 29 -8 2015 14 25 -6 2016 17 28 -9 2017 15 27 -7 2018 18 29 -9 2019 14 26 -7 2020 13 26 -6
What is the coefficient of the dummy variable? What is the meaning of the coefficient of the dummy variable?

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Oil $(x)$	Gasoline $(y)$
60.33	2.188
87.09	2.35
78.12	2.625
82.91	2.627
64.76	2.489
69.58	2.791