In the previous project assignments (Part #1 and #2), you chose a city/region, identified a business idea, discussed the source of the data set and potential issues, and began analyzing variables of interest that might help your business. Now you are ready to review the data set using Inferential Statistics (Chapters 8, 9, 10, and 14).
Pick ONE test from the list below to analyze your AirBnB data set. Once you have run your test, write a short summary of the results and business implications. In other words, what do your findings suggest you should do as a business? Be sure to insert the results from your statistical test in your Word document before submitting.
- Develop confidence interval estimates (per Ch. 8) for a variable of interest and explain why it is useful to a decision maker. For example, I could develop a confidence interval estimate for the average price per night in Montreal Canada or a confidence interval estimate for the proportion of AirBnB listings in the neighborhood of Ville Marie out of all listings in Montreal, Canada. These would be helpful to understand the budget of travelers to Montreal, Canada as well as to see if Ville Marie is a popular vacation rental neighborhood within the city.
- Conduct a hypothesis test (per Ch. 9 or 10) and explain what conclusions you can draw from it and why its useful to your business. For example, I hypothesize that the average price per night stay at Ville Marie in Montreal is $120 because I want to find an upscale neighborhood to open my bike and wine tour business (Ch. 9). Or I could test the hypothesis that the Ville Marie neighborhood costs more per night than the Le Plateau-Mont-Royal neighborhood (Ch. 10). Make sure to explain the components of your hypothesis test such as your null and alternative hypotheses, alpha level, sample size, population mean or proportion, sample mean or proportion, sample standard deviation (if applicable), etc.
- Conduct a Correlation and/or Regression Analysis (per Ch. 14) using two numeric variables from the data set and explain what conclusions you can draw from it and why its useful to your business. For example, I may want to see if there is a correlation between PRICE and ACCOMMODATES (number of people), which can help me make decisions about group pricing for my bike tour. Make sure to explain why you choose the variables you did, and explain the hypothesis test and results.
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