Download Lab 6: Gas Mileage (mini project) The project involves a dataset of

Lab 6: Gas Mileage (mini project)
The project involves a dataset of vehicle fuel consumption (in miles per gallon) for both U.S. A.
and Japanese models. People may think that Japan models have higher mpg, but we may need to
understand how statistically significant the difference is. The best way to understand the
application of statistical procedures and the meaning of the results is to carry out detailed
projects involving data analysis of this kind.
1) Objectives

This individual-based mini project has been designed to prepare you for the requirements
of the final team-based project based on the given data of gas mileage of the US and
Japanese cars
Note
1. The project MUST BE COMPLETED USING MINITAB
2. The project report MUST BE WRITTEN USING ROMAN TIMES FONT, 1.5 point
spacing
3. Download the data into your Minitab file from D2L, and use it for the analysis.
4. Make good section numbering. Make good figures following the tips for good figures.
Make grammatically correct, and well-flowing sentences.
2) Project Procedures
a) Section 1: Introduction
Write two paragraphs (each about 4-6 lines) that introduces and explains the problem.
The importance of the problem and the analysis you are about to perform will come to the
next section. Except for the importance of these, the reader of your report should
understand and agree with what you write here. Here, only data is provided, so make the
problem case creatively. If needed, put figures for the explanation. (However, the figure
should very significantly contribute to the understanding of the problem. For example,
do not put figures of any two cars saying (i) Japanese car (ii) US car.) For this
assignment, if needed, search for the Internet. Before starting writing this, refer to the
data file of gas mileage. Clearly tell the populations you are analyzing.
b) Section 2: Importance
Demonstrate the importance of the problem (problem itself) and the importance of your
research. After reading this, a hypothetical funding agency should agree with the
importance of the research. Write two paragraphs, each longer than six lines.
c) Section 3: Data Collection
The data file is given to you. However, pretend you needed to collect this data by
yourself. Pretend you got this data by your own data collection effort (not from the
Internet or from an ‘expert’). Discuss the data collection method and the sampling
method you (hypothetically) chose. Compare your choice with other possible alternatives,
and justify yours. Also, describe limitations of your data collection method, and possible
bias in your conclusion that will follow. (Making these limitations clear is certainly
needed; however, just listing the limitations without proper analysis and discussion does
not justify weakness of the data collection.)
d) Section 4: Data Presentation
Show the data provided in a table in an appendix. Also, summarize the data to show
some characteristics of your choices. A summary includes the number of samples and the
sample sizes. Use tables and figures you learned in class with a proper format. The
figures will include histograms, frequency polygons, Ogives, and box plots (you can have
the two box-plots in one graph to make comparison). Make these graphs and try to get
useful information from them. Make a few tables and/or graphs. Be creative. Make the
figures look good. Guide the leaders to easily follow your discussion in the text when
you explain the tables and figures. (So, it is not good a good way of using a graph just
saying, “this figure clearly shows my conclusion.”)
Give a table caption at the top. Give a figure caption at the bottom. Choose a right size of
font in a table. Make a proper legend (with one series, do not make a legend), proper
axes labels, and axis ranges (make the figure to fill the entire (x, and y) range of a graph).
e) Section 5: Normality test
As you know, a lot of the statistics analysis is based on the Normality of the populations.
Test normality for both of the populations, US cars and Japanese cars. Use (i) the
histogram + skewness + outlier test and (ii) probability plot test. In the case of
probability plot, tell if the population is normal or skewed, thick tailed and/or thin tailed.
Make clear conclusions about the Normality.
After that, even if the population is not Normal, pretend it is normal and continue the
analysis.
f) Section 6: Confidence Interval Estimation
Estimate these. Show calculations in a proper way.
o Population means of the two populations.
o Population variances of the two populations.
o Difference of the population means of the two populations.
o Ratio of the population variances of the two populations.
g) Section 7: Statistical analysis
Perform these statistic tests. Show calculations in a proper way.
a) Compare the two means.
b) Compare the two variances.
Follow these steps for each test.
a) Write the hypotheses clearly. In the hypotheses, use a mathematical formulas.
(For example, do not say, “the means are the same.” Instead, say, 12.)
b) Write the test statistic formula along with the formula of degree of freedom.
c) Write the TV.
d) Find the p-value.
e) Make a decision at the significance level of 5%.
h) Section 7: Conclusion
What is your take from the mini project?
3) Reference section
Use at least one on-line reference, one book reference (except for any statistics book) and
one journal article reference. Use the I.E.E.E. method of citation and referencing of work
(this is one of the allowable scientific referencing style in journals). This url contains the
I.E.E.E.
referencing
style
requirements.
http://www.ieee.org/documents/ieeecitationref.pdf
A reference section does not have a section number.
4) Appendix
Put the data in this appendix. The data set given is not large, and you may not need to
use an appendix. For this mini project, put it original data here. Use a good format
(number of rows and number of columns, etc.) with a proper title. An appendix does not
have a section name. It comes after the reference.
5) Assignment
Turin in the complete project report to D2l.