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Boston Pre-COVID Tourism Analysis with R.pdf

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Boston Pre-COVID Tourism Analysis with R.pdf

Boston Pre-COVID Tourism Analysis with R:
Data:
https://data.boston.gov/dataset/economic-indicators-legacy-portal
Code:
https://github.com/naoyamorishita/study/blob/7c45e4349ac1e67f785cf187a9803f8336d52f69/boston_precovid_tourism_analysis_withR

Boston Pre-COVID Tourism Analysis with R:
Data:
https://data.boston.gov/dataset/economic-indicators-legacy-portal
Code:
https://github.com/naoyamorishita/study/blob/7c45e4349ac1e67f785cf187a9803f8336d52f69/boston_precovid_tourism_analysis_withR

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Boston Pre-COVID Tourism Analysis with R.pdf

  1. 1. Boston Pre-COVID Tourism Analysis with R Naoya Morishita
  2. 2. Table of Contents • Introduction • Methods • Result • Conclusion
  3. 3. Table of Contents • Introduction • Methods • Result • Conclusion
  4. 4. Objective of Study • To Analyze Relationship between: • Number of Passengers of Boston Logan International Airport • Daily Average Hotel Rate • To Enhance R Analysis Skill
  5. 5. Research Questions üWere there Descriptive Characteristics in the Data? üWere there Statistical Relationships among the Data?
  6. 6. Table of Contents • Introduction • Methods • Result • Conclusion
  7. 7. Dataset • ECONOMIC INDICATORS (CSV) • Including • Total Number of Passengers/ Month at Logan Airport • Total Number of Int’l Flights/ Month at Logan Airport • Average Hotel Rate in Boston Monthly Basis • Downloaded on 16 Nov 2022 • URL is in the Description of this Deck
  8. 8. Research Questions üWere there Descriptive Characteristics in the Data? üWere there Statistical Relationships among the Data?
  9. 9. •Summary •Bar Charts Q1 •Coefficient Constant •Regression Analysis Q2
  10. 10. Table of Contents • Introduction • Methods • Result • Conclusion
  11. 11. Whole Code Available in the Description of This Deck!
  12. 12. Fig 1 Summary of No. of Passengers Summary of Hotel Rate ($)
  13. 13. Fig 2 Yearly No. of Passenger
  14. 14. Fig 3 No. of Passengers & Hotel Rates: Strong Coefficient Single Linear Regression Line
  15. 15. Bad Example! Why?: There is a strong Coefficient between the explanatory variables
  16. 16. Table of Contents • Introduction • Methods • Result • Conclusion
  17. 17. Conclusion • No. of Average Passenger was around 3.5M/ Month • Average Hotel Rate was around $250/ Night • Yearly Number of Passengers of Logan Airport Increased • There was a Strong Correlation between: • No. of Passengers/ Month of Logan Airport • Monthly Average Rate of Hotel/ Night

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