Using the e-commerce data set, answer the following questions in an RMarkdown file:

1. How many observations and variables are in the e-commerce data set?
2. Compute a frequency table for the country of origin for site visits. After the United States, which country had the most visitors?
3. Compute a two-way frequency table for the intent to purchase (intentWasPlanningToBuy), broken out by user profile.
4. What are the proportions of parents who intended to purchase? the proportions of teachers who did? For each one, omit observations for whom the intent is unknown (blank).
5. Among US states (recorded in the variable region), which state had the most visitors and how many?
6. Compute summary statistics for number of site visits.
7. What is the difference in the mean and median for number of site visits?
8. The variable behavPageViews is a factor variable, but we might like to do computations on the number of views. Insert a new variable pageViewInt that is an integer estimate of the number of page views for each row, and add it to ecomm.df. Be conservative with the estimates; for example, when the data say "10+" views, code only as many as are indicated with confidence
9. What is the Pearson's r correlation coefficient between number of visits and the integer estimate of page views? What is the correlation if you use log of visits instead?