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Information about an assignment for a statistics class where students are required to analyze a sample of data to determine the distribution from which it was drawn. The assignment involves calculating the mean and variance of the sample, determining if the random variable is discrete or continuous, and making an inference about the distribution of the population based on the sample. The document also includes instructions for submission and penalties for late submission.
Typology: Exercises
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Assignment 2 (due Thursday, 15 November 2018 at 23:55)
students decide to form a group, they can choose any one student’s data set. You can find your data in the Excel file titled “Assignment 2 data sheet.xlsx” under your student ID number.
points. If it is handed in during the next 24 hours, it will lose another 25 points and so on. Consequently, no points can be gained after 4 days.
Insert any charts/graphic objects here, too (optional). You can adjust the amount of space between the questions to fit your answers. Do not attach Excel or other printouts or hand-written material. You must only submit the Word document, and in Word or pdf format, to Moodle.
reduce file size, you can use the "Reduce File Size" in the File menu Word.
It is sufficient for one person to upload the answers for each team.
Team member names and ID’s: Last Name First Name ID
1. ÇARKÇI BARIŞ 2016300261 2. KAÇMAZ SUİLETEN
I generated a sample of size 1000 for you (different for every person). Your assignment is to try and understand from which distribution your sample was generated. Only the distributions we learned about in class were used. Note that a sample may not have the properties of the entire population. For example, if I randomly picked 100 students from the university and found the mean of their GPA’s, this number will probably not equal the mean GPA of the entire student population at the university. As the sample size gets larger, however, we would expect to get a sample mean GPA to get closer to the population mean GPA.
the parameter value(s). Geometric probability distribution. Probability distribution function : F(x) = P( X x) = P (you get a success at or before the (x +1)th trial ) =1 – P(first (x+1)) trials are all failures) = 1 – (1-p) (x+1) Parameter(s) : p. where 0<p<
following points:
f(x) = (1-p)(x-1)^ * p parameter(s) : p. where 0 < p < 1