Gender and College Major Investigation Task
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Jackson County High School *
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101
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English
Date
Nov 24, 2024
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docx
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Uploaded by ChefAnteater629
Sophie Harris
Gender and College Major Investigation Task
ACADEMIC MAJOR
Art
Sciences
Engineering
Education
Gender
Female
35
15
5
25
Male
19
40
50
20
Numerical Comparison:
How would you describe the SHAPE of the table? Think Matrix Dimension (do not include
headers)! rows x columns
The table above used frequency counts to describe preferences for majors. Two-way
tables show relative frequencies for the whole table. In the Art and Education column,
more females have a major in the field than the males. However, males have a higher
number of majors in Sciences and Engineering. Therefore, this could be used to show
that females have a higher frequency in jobs that often pay less than males. Therefore, I
would describe the shape of the table to be a lot higher for the females than that of
males when shaped on the table.
How would you edit the table to be more useful? What is missing in order to convert raw counts
to percent?
To make the table more useful I could possibly add the totals for each academic major
and genders to easily calculate percentages. The totals are missing in order to convert
raw counts to percentages. Hence, when calculating percentages, we simply need that to
be the denominator to divide the asking proportion by the total number. As a general
rule, when the numerator in count data is very small, or when the denominator is fairly
small, I prefer to see the numerator and the denominator separately rather than a
percentage.
Among male students, what percent are majoring in engineering subjects?
50/129= 38.8%
Among education majors, what percent are males?
20/44= 44.4%
What percent of students are majoring in science?
55/209= 26.3%
What are the marginal distributions by gender? (Choose either male or female.)
The marginal distribution of gender is 209. females 80; male 129.
Do you think that gender and choice of major are related or NOT? Give statistical evidence to
support your claim.
I think that gender and choice of major are related. For instance, for art, 64.8% of
females were taking this major, while only 35.1% of males were. Therefore, more
females were taking this major. On the other hand, engineering for example, showed
that only 0.09% of females were in this major, whereas there were 90.9% males in this
major. Art, in my opinion, is more of a female liking major, whereas engineering is more
for males. Therefore, with these statistics shown, I believe that gender and choice of
major are related.
Geographical Comparison:
One way to display categorical data is through the use of pie charts.
This problem requires TWO
pie charts, one for each gender.
Create and comment on those gender pie charts.
What
features are evident in the graphs?
The gender pie charts portray findings that conclude that there are more females than
males in art, more males in sciences than females, more males interested in engineering,
and lastly, more females in the education major than that of males. Also, we can
conclude that according to the charts, out of the number of female students, there are
more students who are majoring in education compared to the number of male
students. However, there are fewer total female students numerically. Some features
evident in the graphs are the percentages of each major per gender.
2
Formula Method:
Given the formula for EXPECTED counts in any cell to be Expected Frequency = (row total *
column total) / (total of all) Pick any cell and use your findings to either confirm or reject your
previous statement. Explain.
X
X
Academic
Major:
X
X
Art
Science
Engineering
Education
Gender
Female
35
(20.7)
15
(21.1)
5
(21.1)
25
(17.2)
X
Male
19
40
50
20
The numbers in the top cells of the table is the observed frequency and the numbers on the
bottom are the expected frequency. The expected frequencies are shown in parentheses. Thus,
this confirms my previous statement, the actual frequency that was obtained from the table of
row relative frequencies. The sums of the observed frequencies are equal to the sums of the
expected frequencies in each row of the column of the table.
3
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