1. Consider the following scenario As a marketing manager, you are tasked with selecting a website to place your advertisement. The following sampled data shows the number of user visits per month over the last 3 three years: Website 1: 10357, 10537, 10767, 10561, 10544, 10581, 10602, 10665, 10335, 10419, 10737, 10410, 10485, 10601, 10458, 10472, 10435, 10375, 10436, 10510, 10345, 10559, 10520, 10425, 10351, 10465, 10491, 10671, 10366, 10440, 10618, 10606, 10406, 10538, 10449, 10462 Website 2: 11067, 11029, 10888, 10789, 10914, 10663, 10787, 11140, 11042, 11074, 10868, 10853, 10900, 11088, 10991, 10928, 10959, 11126, 11033, 11114, 11150, 11155, 11027, 10900, 11015, 11123, 10953, 11181, 10855, 10731, 10971, 10770, 11070, 11122, 11018, 10903 Since the behavior of internet users can be considered a natural process, consider the number of views to follow normal distribution. In addition, please assume no autocorrelation or time-series nature of the data. Based on the data above, provide the answers to the following questions:
2. What is the average and standard deviation of viewership of each website?
3. Is viewership different between these two websites? If yes, why, and which website provides more views?
4. Suppose that your manager requires at least 12000 views per month. What is the probability of 12000 views happening on each website?
5. Which website provides more consistent view? How would you measure it?
6. If your company definitely needs at least 12000 views, what would be your recommended course of actions?
1. Hints:

• R users can modify codes on lines 213-220 for easy copy-paste of the data above.
• Please keep in mind that viewership is a random variable