Question 2 Quality Issues & Data Cleaning [25 points]:

We have a dataset that is collected from Booking.com for Hotel ratings in a city. A small sample of this dataset is shown below. As we know, every dataset comes with quality issues and this one is no exception. We have talked about TWO main strategies in class to deal with missing data issues: Omission and Imputation. When it comes to Omission, it can be row-wise (deleting one subject) or column-wise (deleting the feature or variable). Therefore, we have three choices here,Row-wise Omission, Column-wise Omission, and Imputation.

1. a) How would you address the missing data issue in this sample dataset employing these strategies? Mention which strategy can be applied for each part of the dataset and why. [15 points]

2. b) Its important to figure out the reason why the data is missing. What do you think could be the possible reason specifically for some of the missing data here? For example: Hotel #3 or Food data. [5 points]

Your Answer:

a)

b)