STA 9708 LN1.D Hmw 1-31-23 (1)

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Baruch College, CUNY *

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9708

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Statistics

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Jan 9, 2024

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docx

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STA 9708, Baruch College, 1-31-23 Prof. L. Tatum LN1.D Homework Exercises Due: Feb 13 , 11:59 PM Please submit your work in a Microsoft Word document, only. Insert your Excel graph into that Word document. Put your name at the top of the first page of your homework. Turn it in early! An Important Alert : when you upload a Word document to Blackboard and then take a look at on the viewing window, your graphs may look messed up. Remain calm, no damage has been to your file. The problem is with the Blackboard viewer. When I see that problem, I simply download the file and open it in Word. Reading assignment : Lecture Note LN1.A . Please try to read through Sections 1-3, several times, on different days . Try to read without fear! Look for concepts that catch your interest, and do not spend time worrying about what to memorize for a test, as there is none. Exercises 1. Go to the posted Stock Excel file, and find your name. Beside your name is the ticker symbol and name of the company assigned to you. Assignments were made randomly, using Excel's rand() function. All the companies are in the S&P500 Index. Follow the instructions in Section 5 , download daily data for your stock from January 1, 2006 to the January 1, 2023 . You should have thousands of rows of data! Continue on, and compute the percentage daily return, as shown in the lecture note. Next, construct a well-formatted time series plot of your daily returns from 2006 to the present. Excel instructions are given in the lecture note in Section 4 . You should have thousands of data points in your graph . In the document you submit, do not show any of the data, just the graph. 2. Review the concept of a population proportion on page 5. Propose an operational definition of the population average for the beverage-expenditure example. ANSWER: In order to obtain the population average for the stated scenario, we would have ask each individual listed on the list of approximately 168.3 million registered U.S. voters about how much they had spent on beverages in the past 30 days. We would then take the mean of the beverage amounts stated, i.e., add up the 168.3 million numeric values stated (X) and divide it by 168.3 million (N). Hence, the population average would be X/N. 3. Review the time series plot on the third page of the lecture note, showing the net weights of the 192 bags of Peanut M&M's. The variation we see there is not due to misbehavior in the underlying system. In the terminology of statistical process control, we would say the variation we are seeing is due to natural variation , meaning variation that was intrinsic in the design of that production line. Such a production line can and will of course fall out-of- control from the time-to-time, perhaps producing a shower of M&M's raining down on to the factory floor instead of into the bags, but that is not happening here.
(a) In your plot of the daily percentage change in price for your stock, do you find periods in which the variation in your data resembles that of the variation in the net weights of the bags? Where? Try to describe the nature of the resemblance. ANSWER: When comparing the graph depicting the variation of the net weight of a bag of M&M’s to the graph depicting the daily returns for SJM stock, some similarities can be noted. Not only do both graphs showcase variations of the variable they are measuring, but both graphs also showcase that the variability is natural. However, the range of variation in the daily returns for SJM stock is greater than the variation the net weight of a bag of M&M’s. (b) What are the most striking differences between the behavior of your data and that of the M&M's? To what sources would you attribute those differences? ANSWER: The most striking difference between the behavior of the SJM data and that of the M&M's is that the range of variation in the daily returns for SJM stock is greater than the variation the net weight of a bag of M&M’s. This may be due to the fact that M&M’s are produced in a more strictly controlled environment such as in a manufacturing plant that usually have a rigid quality control process. Inversely, the environment within which SJM operates can not be as controlled, as the rate of daily returns is dependent on stock price which can fluctuate based on several factors such as the general economy, the political environment, intra-company affairs, etc.
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