(solution) StatCrunch Assignment 1 – Part B (1B) This page explains the

(solution) StatCrunch Assignment 1 – Part B (1B) This page explains the

In this assignment, you will use the StatCrunch U data set that you developed in Module 2 (HWStatCrunch#1) as part of the first StatCrunch assignment.

As you did in StatCrunch Assignment 1B, look at the items in the StatCrunch U survey and develop a question regarding population proportions that can be answered using the survey data you collected. 

Look over the StatCrunch_Assignment_3_0515 document. Answer all the questions in that document using the data I have from the previous documents (#1 and #2). I have also provided a PDF example on how Assignment #3 should look like. 

From the past, I noticed that Course Hero Tutors are just using other people’s work that has already been posted in Course Hero. DO NOT use their data as my data is different from theirs. All the answers in my previous homework’s are highlighted in yellow. 

StatCrunch
Assignment 1 ? Part B (1B)
This page explains the assignment.
The questions you need to answer are on the next page.
A key part of research involves formulating interesting questions then developing a methodology
and collecting appropriate data to answer those questions. The final project in this course will
follow this usual path for research. For this assignment, however, the data is already available
and you must write questions that could have been in the mind of the survey developer that led
to the collection of this data.
For convenience, the survey items are shown below. qattachments_eaf9f12e52170af0ca0fbec432c5c708f1227e26.docx Here are a variety questions (from the StatCrunch website) that could be answered using the
data collected by the student survey: The items below ask you to formulate a question, describe your methodology for answering the
question, carry out the methodology you described, then answer your question. Although not as
detailed, this mirrors the format used in many research reports such as the one due at the end
of the term for this course, in RSCH 202, and capstone courses for some degree programs.
Respond to the following items.
1. In Part A of this assignment, you selected a random sample of 30 StatCrunch U students and
created a StatCrunch file containing data from the above survey for those students. You will use
the StatCrunch data file you created in Part A to complete this assignment. Following the
instructions at the end of Part A, paste your StatCrunch data file in the space below. This will
allow your instructor to see your data. Be sure that your data is properly aligned in columns. qattachments_eaf9f12e52170af0ca0fbec432c5c708f1227e26.docx PASTE YOUR SAMPLE DATA HERE:
1088
1251
8629
10558
11812
12049
16897
17803
19512
22384
24218
24427
24941
26468
29081
30926
31324
31848
33458
33483
34152
37088
37115
37144
37412
38917
39127
40834
43199
43427 Male 1
Female
Male 2
Male 2
Female
Female
Male 4
Female
Female
Female
Male 2
Female
Male 2
Female
Female
Male 3
Female
Male 4
Female
Female
Female
Female
Female
Male 4
Female
Female
Male 4
Female
Male 2
Male 2 12
3
6
8
1
2
16
1
1
1
15
1
11
3
4
15
4
14
4
1
1
1
1
13
2
4
16
1
14
11 0
15
36.5
28.5
12
12
0
15
15
13
0
15
25.5
8
17
0
15
0
18
17
20
15
15
21
15
13
0
15
17
0 0
14.5
8467
0
20
0
0
0
0
0
0
17
0
29.5
0
0
0
0
0
0
0
0
0
15416
23
0
0
0
8215
0 1333
12674
0
6249
2813
0
9424
0
3743
0
2979
0
2592
12307
0
3459
0
6661
14521
5325
3629
0
0
4665
0
14899
3746
5586
3082
3439 3875
1127
1650
1394
1204
1258
1281
4042
6876
5493
0
922
1082
1093
1037
2621
7761
1283 2a. State a single question related to a categorical variable that can be answered using your
survey data and the techniques you have studied thus far in this course. You are encouraged to
develop your own question, but you may use an appropriate question from the StatCrunch
website. The question you use should be about the entire population of StatCrunch U students
?not just about those in the sample. Assume that your sample is representative of the
population.
Question:Is the distribution of males and females equal in sophopmore,freshman,junior and
senior? qattachments_eaf9f12e52170af0ca0fbec432c5c708f1227e26.docx b. Explain the methodology you will use to answer the question you posed. Your explanation
should include answers to the following questions. Do not include your analysis or answers to
your question here?only describe how you will do the analysis. What is the variable of interest?
Variable is the gender across student classification.
What graphical techniques will you use to describe your data?
Bar chart is used to describe the data.
Why are those techniques appropriate for analyzing this data? c. Carry out the methodology described in b above. Use StatCrunch and paste copies of the
graphs/charts from StatCrunch in the space below.
Gender * Classification Crosstabulation
Count
Classification
Freshman
Gender Female
Male Total Student Classification
Freshman
Sophomore
Junior
Senior Sophomore Junior Senior Total 10 2 2 4 18 1 6 1 4 12 11 8 3 8 30 Proportion of female
0.91
0.25
0.67
0.5 qattachments_eaf9f12e52170af0ca0fbec432c5c708f1227e26.docx Proportion of female
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0 Freshman Sophomore Junior Senior d. Based on the results of b and c above, answer your question. Include an explanation of how
you used the graphs and charts to formulate your answer. From the above we can see that the distribution of gender varies across the various student
classification as it is maximum in case of freshman and minimum in case of sophomore. As the
sample size is equal to 30 therefore it would be a better estimate(Central Limit theorem) to
generalise it to the whole population that the distribution of male and female of student
classification varies.
3a. State a single question related to a numerical variable that can be answered using your
survey data and the techniques you have studied thus far in this course. You are encouraged to
develop your own question, but you may use an appropriate question from the StatCrunch
website. The question you use should be about the entire population of StatCrunch U students
?not just about those in the sample. Assume that your sample is representative of the
population.
Question:
What is the mean number of credit hours per student?Is the mean credit hour is less than 15 in
both male and female?Is the mean credit hours for male and female vary significantly at the
0.05 level of significance?
b. Explain the methodology you will use to answer the question you posed. Your explanation
should include answers to the following questions. Do not include your analysis or answers to
your question here?only describe how you will do the analysis. What is the variable of interest?
Variable:Credit Hours What graphical techniques will you use to describe your data?
To compare the mean credit hours across gender we can use the bar graph. qattachments_eaf9f12e52170af0ca0fbec432c5c708f1227e26.docx Why are those techniques appropriate for analyzing this data?
Bar graph will be a good technique to analyses whether the mean credit hours across
gender differ and if the mean credit hours of either male and female is greater than or
less than 15. What numerical measures will you use to describe your data?
Numerical measure-Mean of the credit hours of the male and female. Why are those measures appropriate for analyzing this data?
As we care comparing whether the credit hours vary significantly with respect to the
gender. c. Carry out the methodology described in b above. Use StatCrunch and paste copies of the
graphs/charts and numerical summaries from StatCrunch in the space below.
Bar graph of mean Credit hours of male and female: Mean Credit hour
15
14.5
14
13.5
13
12.5
12
11.5 Female Male We will use independent sample t-test to determine whether the mean credit hours for male and
female differ.
Group Statistics
Gender
Credithours N Mean Std. Deviation Std. Error Mean Male 12 12.58 3.147 .908 Female 18 14.72 2.608 .615 Independent Samples Test qattachments_eaf9f12e52170af0ca0fbec432c5c708f1227e26.docx Levene's Test
for Equality of
Variances t-test for Equality of Means
95% Confidence
Interval of the F Sig. t df Sig. (2- Mean Std. Error tailed) Difference Difference Difference
Lower Upper Credithours Equal
variances 1.184 .286 -2.027 28 .052 -2.139 1.055 -4.301 .023 -1.950 20.587 .065 -2.139 1.097 -4.423 .145 assumed
Equal
variances not
assumed d. Based on the results of b and c above, answer your question. Include an explanation of how
you used the graphs, charts, and numerical summaries to formulate your answer.
Analysis from Graph:
From the bar graph it is clear that the mean credit hours in case of both male and female is less
than 15 because the y-axis value of 15 is not crossed by any of the gender which shows the
mean credit hours of male and female..However for female it is close to 15, which is 14.72.
Determining whether mean credit hours varies significantly across gender?
Null Hypothesis:Ho:µ(male)=µ(female)
Alternative Hypothesis:Ha:µ(male)?µ(female)
µ is the mean credit hours.
Consider the null hypothesis that the mean credit hours for male and female are equal against
the alternative hypothesis that the mean credit hours differ significantly at the 0.05 level of
significance. From the above numerical summaries the p-value is 0.0523 is greater than 0.05
therefore we will conclude that the mean credit hours is equal with respect to gender. qattachments_eaf9f12e52170af0ca0fbec432c5c708f1227e26.docx