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Descriptive Statistics

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Collect at least 30 pieces of numerical (quantitative) metric data (see p.16-18) but no more than an n of 50 (30-50 observations and only one theme). If you have a sample larger than 50 randomly select a subset so your n (sample size) is no more than 50.

From the data, plot a histogram, a stem-and-leaf diagram and an ogive (polygon). Also calculate the mean, median, mode, range, standard deviation, and quartiles of the data. Create a boxplot. Explain what this analysis tells you.

In a separate appendix (or spreadsheet), list all 30-50 observations labeled from 1 to 30 (up to 50 if n=50) so I can duplicate your work if necessary. If you have a category/class in the data with zero observations then try to get rid of the gap by extending the width of the class interval or at the very least explain it in your comments. Histograms and other descriptive statistics should not add to the confusion or generate more questions but should answer and explain the data. Look at your descriptive statistics and ask if there are any questions that would be asked and can you answer them by modifying

See attached file for full problem description.

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Solution Summary

The solution has examples of decriptive statistics and graphs. It can be used as a model of how to present a basic analysis of a data set

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***Please see the attached file.

***See posting 106738 for detailed explanations on how to make the graphs and how to calculate each of the statistics.

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Here's the information you sent me before in the template format. Everything now in the template was in the original document, but all of the explanations on how to do the analyses are left out.

In the section at the beginning called "Population drawn from", I think you're also supposed to add why you're interested in this data. I can't answer that for you, but you could say that you're interested in business, so this data is relevant to that.
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Deliverable 1: Descriptive Statistics

Sampling Methodology:

Description of how the random sample was drawn: The data used here are total United States exports from 2003 by industry (from http://ita.doc.gov/td/industry/otea/usfth/aggregate/ H03T41.html). There are over 450 industries listed, so 50 were chosen at random by generating 50 random numbers (using a random number generator found here: http://graphpad.com/quickcalcs/randomN1.cfm) and only keeping the industries assigned to those numbers (as determined by the row number in the Excel file).

Population drawn from: The population is total US exports in 2003 separated by industry. The variable analyzed here is the value (in millions of dollars) of exports in the different industries.

Sample size: n = 50

Sample data:

Table 1: Sample Data
Units = millions of ...

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