Question 1
Open the dataset “Monet_STAT.xls.” The variables in the data set are:
Price = Sale Price in $ (million) (deflated to 2010 dollars)
Height = Height (inches),
Width = Width (inches),
Signed = Dummy variable = 1 if signed by the artist or not, 0 if not,

The population: There are a total of 430 sales of this artist’s paintings. You have access to this entire set of sales.

Your goal is to obtain a random sample from this Population of 430 paintings USING the instructions in part (a).

a. Obtain a SIMPLE RANDOM sample of size 30 from this population of 430 paintings. To do so, follow these steps: First create (insert) a column to the left of the variable PRICE. In this column type in the formula =RAND(). This formula creates a random number between 0 and 1. Copy this formula down all 430 observations. Next copy all these random numbers into another new, empty column, where you paste the number NOT the formula. Call this new variable SORTER. Next, select all your data (all 430 observations AND the first row of Variable labels AND all columns of variables). Under DATA click sort. In the dialogue box sort by SORTER, in ascending order. Finally, pick the top (first 30) observations. Congratulations! You have now collected your first random sample! [Please save this sample data – I will ask you to use it later in the course.]
b. Run a regression to determine how sale price is affected by the size of the painting and whether it was signed by Monet. (Be careful how you measure size.)
c. Interpret the coefficient of size and the coefficient of signed.
d. Provide a graphical illustration of the relationship between price, size, and signed using your answers to (b)
e. Estimate or predict the sale price for the first observation in your data.
f. Calculate the residual for the observation in (e). Explain why there is a residual in a way that someone who hasn’t studied statistics can understand?
g. Suppose that a new (previously unknown) painting of Monet’s was recently discovered in your aunt’s attic. Your aunt tells you that it is 40” (ht) by 20” (width). Estimate the sale price of this painting, both if the painting were signed and not signed.
h. What is your R-squared? What does this tell you about how well your regression fits the data? Explain this in a sentence in a way that can be understood by someone who doesn’t know statistics.
i. Write down a short paragraph (5 sentences MAX) summarizing all your salient findings in (a) – (h) in a way that someone at Christie’s or Sotheby’s (two large art auction houses) could understand and use to price paintings. Here you are to use the feedback I gave you on how to write short reports of statistical findings we discussed in class.

Question 2
Your goal in this question is to use the time series tools to forecast the sales volume of a stock. Go to finance yahoo and pick a stock (you may need to identify the stock’s abbreviation on the NASDAQ or DOW; for e.g. Microsoft is MSFT). Enter it into the quote look up search function. Then under historical data, download weekly data of that stock for approximately 1 year (so you should have about 52 observations, although I’m not too picky about this number). Focus on the variable “Volume” and “date.”
STOCK I would like to use: Uber Technologies, Inc. (UBER)
a.) Determine the best MOVING AVERAGE model to forecast stock prices. That is, use either the MSE (or MAD) to determine the validity of your model and find a model that best captures your data. (3)
b.) Use your model to predict your chosen stock’s price going forward one week past your data’s range (3)
c.) Use excel to produce a graph with both the forecasted Volume as well as the actual data (3)
d.) Summarize your findings two or three sentences. (3)

Question 3
The dataset “satisfaction_2019_STAT.xls” contains data on customer satisfaction responses from surveying an airline’s customers. The airline wants you to analyze this data to help it improves its customer satisfaction levels. Use the data to answer the following questions, which will in turn help determine how the airline should improve customer satisfaction.
a.) What is the probability that a randomly selected customer is “satisfied” or “neutral/dissatisfied?” (2)
b.) Suppose you know that a customer is “loyal,” are they more likely to be “satisfied” or “neutral/dissatisfied?” (3)
c.) Suppose you know that a customer is a “business” traveler, are they more likely to be “satisfied” or “neutral/dissatisfied?” (3)
d.) Use your answers to the previous questions to determine whether the events “satisfied” and “business” traveler dependent or independent events? Similarly, are the events “satisfied” and “loyal” dependent or independent events? (3)
e.) Use your answers to the previous questions to help the airline determine how it should improve satisfaction. I.e. should it target business travelers or loyal customers? (2)

Question 1 Open the dataset “Monet_STAT.xls.” The variables in th...