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Business Statistics SCMA 1000 Winter 2015 Section 2
Assignment 1

Due Tuesday February 25, 2015

Sampling exercise
The purpose of this exercise is to convey some basic concepts in regards to sampling while at the same time deriving sampling distributions empirically. Deriving sampling distributions empirically works best when there are a large number of samples. The idea here is that each student in the class will create 20 samples for two populations, using two different sampling procedures, for a total of 80 samples. These samples will be combined into common datasets which will be used in class (and made available to all students in the class.
The four sampling contexts will be: 1. Discrete numerical population, sampling without replacement (DNWITHOUT) 2. Discrete numerical population, sampling with replacement (DNWITH) 3. Dichotomous population, sampling without replacement (DWITHOUT) 4. Dichotomous population, sampling with replacement (DWITH)
You will generate 20 samples of 5 observations for each of the four sampling contexts above for a total of 80 samples.
The deliverable for this exercise will be an Excel spreadsheet. The samples from all four sampling contexts are to be recorded and submitted on the same spreadsheet. The exact details of which will be described below. The spreadsheet will be used to record your samples. The spreadsheet will have 80 rows, one row for each sample.
The first two columns (Columns A and B) will be your last name and first name. The entries in these two columns will be the same for all 80 rows. The next column (Column C) will record which population and sampling procedure used. Sampling context | What you put in column C | Discrete numerical population, sampling without replacement | DNWITHOUT | Discrete numerical population, sampling with replacement | DNWITH | Dichotomous population,

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