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Days 1 - 15 You notice that after 6 days, approximately 29 of your employees will be sick and not able to work. You have a huge order you need to fulfill within the next two weeks. Because of this, you want to continue collecting data to determine how many people will have been infected by Day 15. The data for Days 1-15 in the table below. 1 Total number of infected people 1 2 Day Number of initially infected people Number of newly infected people 1 2 1 1 3 2 2 4 4 4 8 5 8 16 6 lb 13 29 7 29 14 43 8 43 19 62 9 62 16 78 10 78 89 11 89 4 93 12 93 2 95 13 95 2 97 14 97 99 15 98 99 15 93 99 5. What do you expect to occur as additional days are recorded in the table? Explain your answer. 6. Make a scatterplot of the data from Days 1-15 that shows the total number of infected people each day. 7. Determine the model and regression equation that best fits this data. How do you know this model is best? 8. Explain why the regression model changed after recording more data for this situation. What other scenarios would result in similar data?

Days 1 - 15 You notice that after 6 days, approximately 29 of your employees will be sick and not able to work. You have a huge order you need to fulfill within the next two weeks. Because of this, you want to continue collecting data to determine how many people will have been infected by Day 15. The data for Days 1-15 in the table below. 1 Total number of infected people 1 2 Day Number of initially infected people Number of newly infected people 1 2 1 1 3 2 2 4 4 4 8 5 8 16 6 lb 13 29 7 29 14 43 8 43 19 62 9 62 16 78 10 78 89 11 89 4 93 12 93 2 95 13 95 2 97 14 97 99 15 98 99 15 93 99 5. What do you expect to occur as additional days are recorded in the table? Explain your answer. 6. Make a scatterplot of the data from Days 1-15 that shows the total number of infected people each day. 7. Determine the model and regression equation that best fits this data. How do you know this model is best? 8. Explain why the regression model changed after recording more data for this situation. What other scenarios would result in similar data?

Advanced Engineering Mathematics
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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Days 1 - 15 You notice that after 6 days, approximately 29 of your employees will be sick and not able to work. You have a huge order you need to fulfill within the next two weeks. Because of this, you want to continue collecting data to determine how many people will have been infected by Day 15. The data for Days 1-15 in the table below. 1 Total number of infected people 1 2 Day Number of initially infected people Number of newly infected people 1 2 1 1 3 2 2 4 4 4 8 5 8 16 6 lb 13 29 7 29 14 43 8 43 19 62 9 62 16 78 10 78 89 11 89 4 93 12 93 2 95 13 95 2 97 14 97 99 15 98 99
Transcribed Image Text:Days 1 - 15 You notice that after 6 days, approximately 29 of your employees will be sick and not able to work. You have a huge order you need to fulfill within the next two weeks. Because of this, you want to continue collecting data to determine how many people will have been infected by Day 15. The data for Days 1-15 in the table below. 1 Total number of infected people 1 2 Day Number of initially infected people Number of newly infected people 1 2 1 1 3 2 2 4 4 4 8 5 8 16 6 lb 13 29 7 29 14 43 8 43 19 62 9 62 16 78 10 78 89 11 89 4 93 12 93 2 95 13 95 2 97 14 97 99 15 98 99
15 93 99 5. What do you expect to occur as additional days are recorded in the table? Explain your answer. 6. Make a scatterplot of the data from Days 1-15 that shows the total number of infected people each day. 7. Determine the model and regression equation that best fits this data. How do you know this model is best? 8. Explain why the regression model changed after recording more data for this situation. What other scenarios would result in similar data?
Transcribed Image Text:15 93 99 5. What do you expect to occur as additional days are recorded in the table? Explain your answer. 6. Make a scatterplot of the data from Days 1-15 that shows the total number of infected people each day. 7. Determine the model and regression equation that best fits this data. How do you know this model is best? 8. Explain why the regression model changed after recording more data for this situation. What other scenarios would result in similar data?
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