Question
I am not able to include datasets...I know you will need them but the data is large and coursehero is not allowing me to send
I am not able to include datasets...I know you will need them but the data is large and coursehero is not allowing me to send a file...please contact me at k..i@gmail.com I will send you the data
Please help me my midterm will end within 1.5 hrs that is by 5:30 pm today
Note: Type your results so that they are clear, organized and neat. Copy and paste any necessary output and graphs from the analysis program of your choice into this document.
Download the Midterm Dataset. Use the Alumni data from the first tab for Questions 1-5.
Data Description
A simple random sample of 500 alumni of a large university were asked how often they read the University's Alumni Magazine. The study recorded their graduation year (GRADYEAR), age (AGE), gender (GENDER), and how often they read the magazine (READ).
- (10 points) Treat GRADYEAR as a quantitative variable. Summarize the distribution of GRADYEAR for a manager.Note any interesting aspects of the distribution and report any statistics that would help the manager understand it better. You may include visualizations if they would add to managerial understanding.
- (10 points) Create the contingency table below displaying AGEvs. READ. (Delete the one displayed here and paste the one you create in its place!) Create an appropriate visualization to display the data for a manager.
Age | How often do they read the magazine? | ||||
0 - Never | 1 - Rarely | 2 - Occasionally | 3 - Regularly | 4 - Always | |
24 and below | |||||
25 to 34 | |||||
35 to 49 | |||||
50 to 64 | |||||
65 and over |
- (15 points) Write a short paragraph to a manager explaining any interesting inferences that can be drawn about Age, how often the magazine is read, and the association of the two variables.
Use the Diamonds dataset on the second tab of the data file.
Big T Jewelers is a local jewelry shop that is thinking of getting into the retail diamond business. As part of their pricing strategy, they have obtained a dataset that lists the characteristics and retail sale prices of over 2,000 unset diamonds that were sold at retail in the area. You work for Foxy Consulting, which has been hired by Big T. Big T wants to know whether they can use the information in the dataset to help better understand the relationship between the attributes of a diamond and its price.
- (5 points) Would it be reasonable to model Carat Weight using a normal distribution (i.e., use a normal probability model for the data)? Explain your rationale to your (analytically competent) manager. You want to impress her, so try to list multiple criteria, if possible, so that she is sure that you understand your reasoning.
- (10 points) The cut of a diamond is judged by gemologists on a five level scale: Excellent, Very Good, Good, Fair, Poor.[1] In this dataset, is there a relationship between Cut and price? Using only techniques that we have covered so far in class, write a very short, managerial summary of your findings. You may include a well-formatted visualization if it aids managerial understanding.
- Model the relationship between diamond size (measured in carat weight) and price.
- (20 points) Write a short managerial summary of your findings that would be appropriate if you were writing to your client and your manager at Foxy Consulting. Your manager is an analytics expert, and she wants to make sure that the model is appropriate and that you understand its interpretation so that you can later present it to the client. Be sure to check assumptions.
- (5 points) The client wants to understand what the average difference in eventual sales price would be between a 1.25 and a 1.5 ct diamond. Write an appropriate response.
- (5 points)The client got a cool new diamond in stock that is 2.15 carats in weight. She wants to know the likely sale price of this diamond. Write a managerially appropriate response to the client.
[1]In practice, "poor" cut diamonds are not usually sold as gemstones.
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