Suppose the following data set contains the monthly adjusted stock prices for technology company A, and a consumer-goods company B from 2013–2018. Copy and paste the data into Excel and use the Excel functions for covariance and correlation to solve the question. Date A B 6/1/2013 46.44 67.71 7/1/2013 52.71 70.54 8/1/2013 56.60 68.98 9/1/2013 59.00 67.00 10/1/2013 63.40 71.44 11/1/2013 67.32 74.99 12/1/2013 70.69 72.55 1/1/2014 63.29 68.40 2/1/2014 66.43 70.68 3/1/2014 70.57 72.38 4/1/2014 77.39 74.08 5/1/2014 82.87 73.11 6/1/2014 88.47 71.17 7/1/2014 90.95 69.05 8/1/2014 97.37 75.73 9/1/2014 96.21 76.29 10/1/2014 102.99 79.42 11/1/2014 113.21 82.84 12/1/2014 105.66 83.43 1/1/2015 112.03 77.35 2/1/2015 122.64 78.64 3/1/2015 119.32 75.77 4/1/2015 120.00 73.58 5/1/2015 124.84 73.14 6/1/2015 120.76 73.01 7/1/2015 116.85 71.61 8/1/2015 108.91 66.66 9/1/2015 106.91 67.82 10/1/2015 115.66 71.89 11/1/2015 114.51 71.09 12/1/2015 102.54 75.31 1/1/2016 94.98 77.42 2/1/2016 94.35 76.77 3/1/2016 106.67 78.65 4/1/2016 91.02 76.61 5/1/2016 97.90 78.09 6/1/2016 94.37 81.49 7/1/2016 102.69 81.36 8/1/2016 104.51 84.62 9/1/2016 111.82 86.92 10/1/2016 112.30 84.13 11/1/2016 109.36 80.63 12/1/2016 115.09 82.17 1/1/2017 120.49 85.53 2/1/2017 135.76 89.53 3/1/2017 142.88 88.35 4/1/2017 142.87 85.93 5/1/2017 151.80 85.31 6/1/2017 143.82 86.40 7/1/2017 148.45 90.95 8/1/2017 163.49 92.06 9/1/2017 154.36 89.80 10/1/2017 169.11 84.27 11/1/2017 172.88 87.49 12/1/2017 169.90 92.35 1/1/2018 168.11 86.90 2/1/2018 178.72 76.80 3/1/2018 169.14 77.55 4/1/2018 166.63 75.68 5/1/2018 189.86 86.31 (c) Compute the sample covariance. (Round your answer to two decimal places.) Interpret the sample covariance. 1. There is a positive relationship between the two variables. 2. There is a negative relationship between the two variables. 3. There is no relationship between the two variables. (d) Compute the sample correlation coefficient. (Round your answer to two decimal places.) What does this value indicate about the relationship between the stock price of company A and the stock price of company B? 1. There is a moderately strong positive relationship between the two variables. 2. There is a moderately strong negative relationship between the two variables. 3. There is no relationship between the two variables. 4. There is a positive relationship between the two variables, but the strength of this relationship cannot be determined based on the sample correlation coefficient. 5. There is a negative relationship between the two variables, but the strength of this relationship cannot be determined based on the sample correlation coefficient.
Suppose the following data set contains the monthly adjusted stock prices for technology company A, and a consumer-goods company B from 2013–2018. Copy and paste the data into Excel and use the Excel functions for covariance and correlation to solve the question. Date A B 6/1/2013 46.44 67.71 7/1/2013 52.71 70.54 8/1/2013 56.60 68.98 9/1/2013 59.00 67.00 10/1/2013 63.40 71.44 11/1/2013 67.32 74.99 12/1/2013 70.69 72.55 1/1/2014 63.29 68.40 2/1/2014 66.43 70.68 3/1/2014 70.57 72.38 4/1/2014 77.39 74.08 5/1/2014 82.87 73.11 6/1/2014 88.47 71.17 7/1/2014 90.95 69.05 8/1/2014 97.37 75.73 9/1/2014 96.21 76.29 10/1/2014 102.99 79.42 11/1/2014 113.21 82.84 12/1/2014 105.66 83.43 1/1/2015 112.03 77.35 2/1/2015 122.64 78.64 3/1/2015 119.32 75.77 4/1/2015 120.00 73.58 5/1/2015 124.84 73.14 6/1/2015 120.76 73.01 7/1/2015 116.85 71.61 8/1/2015 108.91 66.66 9/1/2015 106.91 67.82 10/1/2015 115.66 71.89 11/1/2015 114.51 71.09 12/1/2015 102.54 75.31 1/1/2016 94.98 77.42 2/1/2016 94.35 76.77 3/1/2016 106.67 78.65 4/1/2016 91.02 76.61 5/1/2016 97.90 78.09 6/1/2016 94.37 81.49 7/1/2016 102.69 81.36 8/1/2016 104.51 84.62 9/1/2016 111.82 86.92 10/1/2016 112.30 84.13 11/1/2016 109.36 80.63 12/1/2016 115.09 82.17 1/1/2017 120.49 85.53 2/1/2017 135.76 89.53 3/1/2017 142.88 88.35 4/1/2017 142.87 85.93 5/1/2017 151.80 85.31 6/1/2017 143.82 86.40 7/1/2017 148.45 90.95 8/1/2017 163.49 92.06 9/1/2017 154.36 89.80 10/1/2017 169.11 84.27 11/1/2017 172.88 87.49 12/1/2017 169.90 92.35 1/1/2018 168.11 86.90 2/1/2018 178.72 76.80 3/1/2018 169.14 77.55 4/1/2018 166.63 75.68 5/1/2018 189.86 86.31 (c) Compute the sample covariance. (Round your answer to two decimal places.) Interpret the sample covariance. 1. There is a positive relationship between the two variables. 2. There is a negative relationship between the two variables. 3. There is no relationship between the two variables. (d) Compute the sample correlation coefficient. (Round your answer to two decimal places.) What does this value indicate about the relationship between the stock price of company A and the stock price of company B? 1. There is a moderately strong positive relationship between the two variables. 2. There is a moderately strong negative relationship between the two variables. 3. There is no relationship between the two variables. 4. There is a positive relationship between the two variables, but the strength of this relationship cannot be determined based on the sample correlation coefficient. 5. There is a negative relationship between the two variables, but the strength of this relationship cannot be determined based on the sample correlation coefficient.
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.5: Correlation And Causation
Problem 23PFA
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Suppose the following data set contains the monthly adjusted stock prices for technology company A, and a consumer-goods company B from 2013–2018. Copy and paste the data into Excel and use the Excel
| Date | A | B |
| 6/1/2013 | 46.44 | 67.71 |
| 7/1/2013 | 52.71 | 70.54 |
| 8/1/2013 | 56.60 | 68.98 |
| 9/1/2013 | 59.00 | 67.00 |
| 10/1/2013 | 63.40 | 71.44 |
| 11/1/2013 | 67.32 | 74.99 |
| 12/1/2013 | 70.69 | 72.55 |
| 1/1/2014 | 63.29 | 68.40 |
| 2/1/2014 | 66.43 | 70.68 |
| 3/1/2014 | 70.57 | 72.38 |
| 4/1/2014 | 77.39 | 74.08 |
| 5/1/2014 | 82.87 | 73.11 |
| 6/1/2014 | 88.47 | 71.17 |
| 7/1/2014 | 90.95 | 69.05 |
| 8/1/2014 | 97.37 | 75.73 |
| 9/1/2014 | 96.21 | 76.29 |
| 10/1/2014 | 102.99 | 79.42 |
| 11/1/2014 | 113.21 | 82.84 |
| 12/1/2014 | 105.66 | 83.43 |
| 1/1/2015 | 112.03 | 77.35 |
| 2/1/2015 | 122.64 | 78.64 |
| 3/1/2015 | 119.32 | 75.77 |
| 4/1/2015 | 120.00 | 73.58 |
| 5/1/2015 | 124.84 | 73.14 |
| 6/1/2015 | 120.76 | 73.01 |
| 7/1/2015 | 116.85 | 71.61 |
| 8/1/2015 | 108.91 | 66.66 |
| 9/1/2015 | 106.91 | 67.82 |
| 10/1/2015 | 115.66 | 71.89 |
| 11/1/2015 | 114.51 | 71.09 |
| 12/1/2015 | 102.54 | 75.31 |
| 1/1/2016 | 94.98 | 77.42 |
| 2/1/2016 | 94.35 | 76.77 |
| 3/1/2016 | 106.67 | 78.65 |
| 4/1/2016 | 91.02 | 76.61 |
| 5/1/2016 | 97.90 | 78.09 |
| 6/1/2016 | 94.37 | 81.49 |
| 7/1/2016 | 102.69 | 81.36 |
| 8/1/2016 | 104.51 | 84.62 |
| 9/1/2016 | 111.82 | 86.92 |
| 10/1/2016 | 112.30 | 84.13 |
| 11/1/2016 | 109.36 | 80.63 |
| 12/1/2016 | 115.09 | 82.17 |
| 1/1/2017 | 120.49 | 85.53 |
| 2/1/2017 | 135.76 | 89.53 |
| 3/1/2017 | 142.88 | 88.35 |
| 4/1/2017 | 142.87 | 85.93 |
| 5/1/2017 | 151.80 | 85.31 |
| 6/1/2017 | 143.82 | 86.40 |
| 7/1/2017 | 148.45 | 90.95 |
| 8/1/2017 | 163.49 | 92.06 |
| 9/1/2017 | 154.36 | 89.80 |
| 10/1/2017 | 169.11 | 84.27 |
| 11/1/2017 | 172.88 | 87.49 |
| 12/1/2017 | 169.90 | 92.35 |
| 1/1/2018 | 168.11 | 86.90 |
| 2/1/2018 | 178.72 | 76.80 |
| 3/1/2018 | 169.14 | 77.55 |
| 4/1/2018 | 166.63 | 75.68 |
| 5/1/2018 | 189.86 | 86.31 |
(c) Compute the sample covariance. (Round your answer to two decimal places.)
Interpret the sample covariance.
1. There is a positive relationship between the two variables.
2. There is a negative relationship between the two variables.
3. There is no relationship between the two variables.
(d) Compute the sample correlation coefficient . (Round your answer to two decimal places.)
What does this value indicate about the relationship between the stock price of company A and the stock price of company B?
1. There is a moderately strong positive relationship between the two variables.
2. There is a moderately strong negative relationship between the two variables.
3. There is no relationship between the two variables.
4. There is a positive relationship between the two variables, but the strength of this relationship cannot be determined based on the sample correlation coefficient.
5. There is a negative relationship between the two variables, but the strength of this relationship cannot be determined based on the sample correlation coefficient.
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