TypeFord edge
Ford Escape
Ford Expedition
Ford Explorer
Ford fusion
Ford Mustang
Chevy Blazer
Chevy Trax
Chevy Bolt
Chevy Camaro
Chevy Corvette
Chevy Equinox
Chevy Impala
Chevy Malibu
Chevy Sonic
Chevy Spark
Chevy Suburban
Chevy Tahoe
Chevy Traverse
Audi A3
Audi A4
Audi A5
Audi A6
Audi A7
Audi A8
Audi E-Tron
Audi Q3
Audi Q5
AudiQ7
Audi Q8
Audi TT
Milages Seating
24
5
16
5
23
9
25
7
22
5
17
4
19
5
25
5
119
5
20
4
20
2
31
5
22
5
32
5
28
5
33
4
16
9
20
9
25
8
27
5
27
5
17
4
25
5
25
5
21
5
74
5
22
5
24
5
20
5
19
5
26
4
milages
seating
sample size
mean
SD
min
Q1
median
Q3
max
31
31
27.87096774 5.290322581
19.71419444 1.553352254
16
2
20
5
24
5
26.5
5
119
9
Type
Ford
Chevy
Audi
Total
Frequency
Proportion
6
0.1935
13
0.4194
12
0.3871
31
1
Frequency BarChart Type Vehicle
14
12
10
8
6
4
2
0
Ford
Chevy
95% CI
Mode
n
x
25
31
9
p-hat
0.290323
SE
0.081525
E
0.159786
Lower
Upper
0.131
0.450
y BarChart Type Vehicle
Chevy
Audi
Project Part 5 – Confidence Interval for µ
Points on Rubric: 20 Submit as a file upload
Use your data set from Part 2 of the Project and your summary statistics from Part 3, to complete
this part of the project. Place your results in a semi-professional looking report. Remember to
include your name, date, title, page numbers, etc.
Your goal for this portion of the project is to select one of your quantitative variables (the one
that you would be most interested in predicting) and use your data to create and interpret a
confidence interval for the population mean. Please review the comments and/or feedback that I
provided on Projects Parts 1, 2, and 3. Do not repeat previous mistakes.
If there were any invalid responses in your data, you need to eliminate these responses from your
sample and mention that this was done in the introduction or conclusion of your paper.
Your report will be short, but must include these three parts:
Part 1: Introduction Provide a short introduction to the project. Specifically, briefly describe
the sample, your variable (including the units of measurement), the target population, and what
you will analyze in the project.
Part 2: Confidence Interval for µ. List the summary statistics for your each of your QN
variables. (i.e. sample average, sample standard deviation, sample size, and anything else you
would like to include) for your quantitative variable (include your units of measurement). Note:
This is mostly a repeat of part 3 of this Project
Part 3. Create a 95% CI for the true mean of your quantitative variables.
(a) Practically interpret these confidence intervals.
(b). Theoretically interpret the phrase “95% confident.”
Part 4: Conclusion Provide a short conclusion. Your conclusion may include assumptions you
have made, potential problems with the analysis, what you learned, or anything else you want to
say to tie the results together neatly.
Part 5 Sample RESPONSE Example:
Your NAME
MAT 201- CAxxx
Instructor: Dr. Charlotte A. Smedberg
03/09/2021
Project Part 5 – Confidence Interval for Population Mean
Introduction:
In this project, I chose to use a sample of 58 SLU University Campus students to predict the
(US) shoe size of all SLU students. The results revealed the following data:
Summary Statistics for each variable :
Column n
Shoe
Size
Column
Mean
Variance Std. dev.
Std. err.
Median Min Max Q1 Q3
58 8.2586207 7.3091349 2.7035412 0.35499235
n
Mean Variance Std. dev.
head Size 58 9.7348 1.561349
Std. err.
2.75412 0.35499235
8
2.5
13 6.5 10.5
Median Min Max Q1 Q3
7
2.5
13 6.5 10.5
Confidence Interval for each variable:
The 95% confidence interval for μ is (7.6, 9.0). for (variable name) You need two of these
Practical Interpretation:
I am 95% confident that the true mean shoe size for all SLU students is between 7.6 and 9.0 US.
A second statement for other variable
Theoretical Interpretation:
In repeated sampling distributions, 95% of similarly constructed confidence intervals will
capture μ, and 5% will miss.
Conclusion:
While I successfully created a confidence interval that predicts the shoe size of all SLU students,
there were some issues discovered in the survey design and student selection that could cause
biased results. Only students in three statistics classes at the University campus were analyzed,
and these students might be not representative of the entire student body at SLU. In addition,
some female students reported their shoe size in US female shoe sizes, while others reported
their shoe size as children or male shoe sizes. Therefore the results may not reflect the true mean
of the students at SLU.
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