MATH 225N WEEK 8 QUESTIONS WITH ANSWERS
Performing Linear Regressions with Technology
1.An amateur astronomer is researching statistical properties of known stars using a variety of databases. They collect the absol
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MATH 225N WEEK 8 QUESTIONS WITH ANSWERS
Performing Linear Regressions with Technology
1.An amateur astronomer is researching statistical properties of known stars using a variety of databases. They collect the absolute magnitude or MV and stellar mass or M⊙ for 30 stars. The absolute magnitude of a star is the intensity of light that would be observed from the star at a distance of 10 parsecs from the star. This is measured in terms of a particular band of the light spectrum, indicated by the subscript letter, which in this case is V for the visual light spectrum. The scale is logarithmic and an MV that is 1 less than another comes from a star that is 10 times more luminous than the other. The stellar mass of a star is how many times the sun's mass it has. The data is provided below. Use Excel to calculate the correlation coefficient r between the two data sets, rounding to two decimal places.
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Correct! You nailed it.
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r= −0.93
Answer Explanation
The correlation coefficient, rounded to two decimal places, is r≈−0.93.
2.A market researcher looked at the quarterly sales revenue for a large e-commerce store and for a large brick-and-mortar retailer over the same period. The researcher recorded the revenue in millions of dollars for 30 quarters. The data are provided below. Use Excel to calculate the correlation coefficient r between the two data sets. Round your answer to two decimal places.
Yes that's right. Keep it up!
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r= −0.81
Answer Explanation
The correlation coefficient, rounded to two decimal places, is r≈−0.81.
3.The table below contains the geographic latitudes, x, and average January temperatures, y, of 20cities. Use Excel to find the best fit linear regression equation. Round the slope and intercept to two decimal places.
x
y
46
23
32
60
39
40
33
59
38
57
40
33
42
33
30
64
34
56
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Yes that's right. Keep it up!
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y = −2.68, x147.24
Thus, the equation of line of best fit with slope and intercept rounded to two decimal places is yˆ=−2.68x+147.24.
4.An organization collects information on the life expectancy (in years) of a person in certain countries and the fertility rate per woman in those countries. The data for 21 randomly selected countries for the year 2011 is given below. Use Excel to find the best fit linear regression equation, where fertility rate is the explanatory variable. Round the slope and intercept to two decimal places.
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y = −4.21, x 83.68 Answer Explanationyˆ=−4.21, x+83.68.
5.An economist is trying to understand whether there is a strong link between CEO pay ratio and corporate revenue. The economist gathered data including the CEO pay ratio and corporate revenue for 30 companies for a particular year. The pay ratio data is reported by the companies and represents the ratio of CEO compensation to the median employee salary. The data are provided below. Use Excel to calculate the correlation coefficient r between the two data sets. Round your answer to two decimal places.
Perfect. Your hard work is paying off ?
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r= −0.17
The correlation coefficient, rounded to two decimal places, is r≈−0.17.
6.A researcher is interested in whether the variation in the size of human beings is proportional throughout each part of the human. To partly answer this question they looked at the correlation between the foot length (in millimeters) and height (in centimeters) of 30 randomly selected adult males. The data is provided below. Use Excel to calculate the correlation coefficient r between the two data sets. Round your answer to two decimal places.
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Great work! That's correct.
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r= 0.50
The correlation coefficient, rounded to two decimal places, is r≈0.50.
7.The table below gives the average weight (in kilograms) of certain people ages 1–20. Use Excel to find the best fit linear regression equation, where age is the explanatory variable. Round the slope and intercept to two decimal places.
Answer 1:
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That's not right - let's review the answer.
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y = 0.35, x28.99
Answer 2:
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Well done! You got it right.
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y = 2.89, x 4.69
Thus, the equation of line of best fit with slope and intercept rounded to two decimal places is yˆ=2.86x+4.69.
8.In the following table, the age (in years) of the respondents is given as the x value, and the earnings (in thousands of dollars) of the respondents are given as the y value. Use Excel to find the best fit linear regression equation in thousands of dollars. Round the slope and intercept to three decimal places.
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Yes that's right. Keep it up!
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y = 0.433, x=24.493
Answer Explanation
Thus, the equation of line of best fit with slope and intercept rounded to three decimal places is yˆ=0.433x+24.493.
PREDICITONS USING LINEAR REGRESSION
Question 9
The table shows data collected on the relationship between the time spent studying per day and the time spent reading per day. The line of best fit for the data is yˆ=0.16x+36.2. Assume the line of best fit is significant and there is a strong linear relationship between the variables.
Studying (Minutes) 507090110 Reading (Minutes) 44485054
(a) According to the line of best fit, what would be the predicted number of minutes spent reading for someone who spent 67 minutes studying? Round your answer to two decimal places.
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Yes that's right. Keep it up!
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The predicted number of minutes spent reading is $$46.92.
Answer Explanation
The predicted number of minutes spent reading is 1$$.
Correct answers:
• 46.92
Substitute 67 for x into the line of best fit to estimate the number of minutes spent reading for someone who spent 67 minutes studying: yˆ=0.16(67)+36.2=46.92.
Question 10
The table shows data collected on the relationship between the time spent studying per day and the time spent reading per day. The line of best fit for the data is yˆ=0.16x+36.2.
Studying (Minutes) 507090110 Reading (Minutes) 44485054
(a) According to the line of best fit, the predicted number of minutes spent reading for someone who spent 67minutes studying is 46.92.
(b) Is it reasonable to use this line of best fit to make the above prediction?
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That's incorrect - mistakes are part of learning. Keep trying!
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The estimate, a predicted time of 46.92 minutes, is both reliable and reasonable.
The estimate, a predicted time of 46.92 minutes, is both unreliable and unreasonable.
The estimate, a predicted time of 46.92 minutes, is reliable but unreasonable.
The estimate, a predicted time of 46.92 minutes, is unreliable but reasonable.
Answer Explanation
Correct answer:
The estimate, a predicted time of 46.92 minutes, is both reliable and reasonable.
The data in the table only includes studying times between 50 and 110 minutes, so the line of best fit gives reliable and reasonable predictions for values of x between 50 and 110. Since 67 is between these values, the estimate is both reliable and reasonable.
......................Continued.............
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