STAT 2060 Lecture Notes - Lecture 24: Shot Put, Summary Statistics, Informa

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23 Nov 2017
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Course
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STAT*2060: Statistics for Business Decisions
Fall 2017
Data Analysis Project #2
Important information and instructions
The deadline for this project is Friday, November 24 at 11:59pm. Late submissions are not
accepted, and will receive a grade of 0.
There are three questions; you must complete all of them. The breakdown of marks for each
question is as follows:
Question 1: 5 marks
Question 2: 10 marks
Question 3: 10 marks
This project is worth 6% of your final grade. You will be assessed on:
getting the proper Excel output and plots (note: you must use Excel for this project!)
validity of your statistical conclusions and interpretations
writing style, including spelling and grammar
presentation
Final report formatting and submission instructions are found at the end of this document. Please
read this information carefully! Projects that do not follow the correct format, or that are not
submitted properly, will not receive full marks.
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1. The distances (in metres) of throws by 20 randomly selected senior male athletes who competed in
the shot-put in in June 1991 are recorded in the file Shotput Data.xlsx, available on Courselink.
Download this data and use it to conduct the following analysis:
(a) Create a histogram of the data, using the instructions found in Data Analysis Project #1.
Be sure to include appropriate an appropriate title and axis label on your plot. Comment
on the shape of the data. Your comments can include things such as symmetry, presence of
outliers, etc. Include both the histogram and your commentary in your final report.
(b) Use Excel to calculate the summary statistics of mean and standard deviation for the data
set. Include these values in your final report. You are not required to show formulas, only
the final values.
(c) Calculate a 95% confidence interval for the true mean distance of shot-put throws by senior
male athletes . What assumptions are required for the conclusions from this procedure to be
valid? Was it reasonable for you to make these assumptions? Include the confidence interval,
an appropriate interpretation, and any comments on assumptions in your final report. You
need to show enough work that someone reading your report can reasonably follow your train
of thought.
(d) The standard deviation you calculated previously is for data sampled in 1991. Let’s assume
we can take this standard deviation to be the population standard deviation of distances of
shot-put throws by male athletes competing today (ignoring any effect of improved training,
equipment, etc.). Suppose you wanted to estimate the mean distance of shot-put throws by
male athletes, with a margin of error of 0.25 metres and 95% confidence. How many athletes
would you have to sample? You need to show enough work that someone reading your report
can reasonably follow your train of thought.
2. This question is based on data found in the article:
Ondogan, Ziynet; Pamuk, Oktay; Ondogan, Ece Nuket; and Ozguney, Arif. (2005). Improving
the appearance of all textile products from clothing to home textile using laser technology. Optics
& Laser Technology 37: 631 - 637.
You will need to obtain a copy of this article through the University of Guelph Library. The data
from this article can be found in the file BlueJeans Data.csv, available on Courselink. Download
this file, and perform the following analysis. (Note: you may wish to first save the file as a .xlsx
file):
(a) Review the article so that you are familiar with the experiment that was conducted.
(b) First, you will need to re-organize the data set so that it appears like Table 1 from the paper.
To do this:
Cut all the rows/columns that correspond to sampleid equal to 2, and paste them beside
the rows/columns that correspond to sampleid equals 1. This essentially means you are
cutting rows #42 - #81 inclusive, and pasting them starting in cell F2.
Repeat this for all the rows/columns corresponding to sampleid equals 3.
Cut and paste the column labels found in Row 1, A - E, to columns F - J and again from
K - O.
You can then delete the repeat columns of method,jeanid and sampleid found in
Columns F - H and K - M.
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