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Answer each of the following two problems (1) using regression analysis (easiest way is using the scatter diagram approach. But you can also use the regression analysis routine in the Data Analysis module in Excel Bus and subway ridership in Washington, D.C., dur- ing the summer months is believed to be heavily tied to the number of tourists visiting the city. During the past 12 years, the following data have been obtained: YEAR 1 2 3 4 5 6 7 8 9 10 11 12 NUMBER OF TOURISTS (1,000,000s) 7 2 6 14 15 16 12 14 20 15 7 RIDERSHIP (100,000s) 15 10 13 15 25 27 24 20 27 44 34 17 (a) Plot these data and determine if a linear model is reasonable. (b) Develop a regression modele (c) What is expected ridership if 10 million tourists visit the city? (d) If there are no tourists at all, explain the predicted ridership.

Answer each of the following two problems (1) using regression analysis (easiest way is using the scatter diagram approach. But you can also use the regression analysis routine in the Data Analysis module in Excel Bus and subway ridership in Washington, D.C., dur- ing the summer months is believed to be heavily tied to the number of tourists visiting the city. During the past 12 years, the following data have been obtained: YEAR 1 2 3 4 5 6 7 8 9 10 11 12 NUMBER OF TOURISTS (1,000,000s) 7 2 6 14 15 16 12 14 20 15 7 RIDERSHIP (100,000s) 15 10 13 15 25 27 24 20 27 44 34 17 (a) Plot these data and determine if a linear model is reasonable. (b) Develop a regression modele (c) What is expected ridership if 10 million tourists visit the city? (d) If there are no tourists at all, explain the predicted ridership.

Practical Management Science
Practical Management Science
6th Edition
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter2: Introduction To Spreadsheet Modeling
Section: Chapter Questions
Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...
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**Regression Analysis Exercise on Tourist and Ridership Data** **Overview:** In this exercise, we explore the relationship between the number of tourists and bus and subway ridership in Washington, D.C. during the summer months. You will apply regression analysis using the following dataset collected over 12 years. **Dataset:** | Year | Number of Tourists (1,000,000s) | Ridership (100,000s) | |------|-------------------------------|---------------------| | 1 | 7 | 15 | | 2 | 2 | 10 | | 3 | 6 | 13 | | 4 | 4 | 15 | | 5 | 14 | 25 | | 6 | 15 | 27 | | 7 | 16 | 24 | | 8 | 12 | 20 | | 9 | 14 | 27 | | 10 | 20 | 44 | | 11 | 15 | 34 | | 12 | 7 | 17 | **Tasks:** (a) **Plot the data** and assess if a linear model is reasonable. (b) **Develop a regression model** to describe the relationship. (c) **Predict ridership** if 10 million tourists visit the city. (d) **Analyze the impact of having no tourists** on predicted ridership. By applying the scatter diagram or the regression analysis tool in Excel, you can establish insights into the correlation between tourist numbers and ridership, aiding urban transit planning and tourism management.
Transcribed Image Text:**Regression Analysis Exercise on Tourist and Ridership Data** **Overview:** In this exercise, we explore the relationship between the number of tourists and bus and subway ridership in Washington, D.C. during the summer months. You will apply regression analysis using the following dataset collected over 12 years. **Dataset:** | Year | Number of Tourists (1,000,000s) | Ridership (100,000s) | |------|-------------------------------|---------------------| | 1 | 7 | 15 | | 2 | 2 | 10 | | 3 | 6 | 13 | | 4 | 4 | 15 | | 5 | 14 | 25 | | 6 | 15 | 27 | | 7 | 16 | 24 | | 8 | 12 | 20 | | 9 | 14 | 27 | | 10 | 20 | 44 | | 11 | 15 | 34 | | 12 | 7 | 17 | **Tasks:** (a) **Plot the data** and assess if a linear model is reasonable. (b) **Develop a regression model** to describe the relationship. (c) **Predict ridership** if 10 million tourists visit the city. (d) **Analyze the impact of having no tourists** on predicted ridership. By applying the scatter diagram or the regression analysis tool in Excel, you can establish insights into the correlation between tourist numbers and ridership, aiding urban transit planning and tourism management.
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