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Census 3

For this assignment we are introducing the ideas and practicing for the concept in the paper we are writing next month.
There is a growing gap in most social indicators; wealth, upward mobility, etc, and education.
There is a common theme in academic writing that Hispanic and black students are underperforming and that poverty also has a strong correlation to school performance.
Let’s do a case study for Miami.

Pretend as though we are working for the Miami-Dade department of education and we need to improve performance for our constituents.
Let’s prepare an executive summary for the education board of which areas we are not succeeding and need to improve.

Step 1 collecting data
All data is at the county subdivision geography.
All data is 2014 ACS 5 year estimates.
We will also want to know male vs female.

1. Find as a whole number the total population 18-24, male 18-24, and female 18-24.
Find as a percent the 18-24 population with no diploma, male percent no diploma, and female percent no diploma.
See example.

2. The next part is going to only be as whole numbers but we have to turn it into different percent’s.
We need to find the total population, poverty pop, male poverty pop, male 18-24, female poverty pop, female 18-24 poverty pop LATIN total population, poverty pop, male poverty pop, male 18-24, female poverty pop, female 18-24 poverty pop Black total population, poverty pop, male poverty pop, male 18-24, female poverty pop, female 18-24 poverty pop
See example.

3. Add the no diploma data. See example
4. We need this table to fit onto a page.
Open a new sheet in your excel book.
Copy your table with all of the data BUT when you paste it there are options, use transpose and it will invert the data.
See example

These have all been my suggestions to you, students, who are learning how to prepare data.
You need to work on making data and visuals that work for you. When you write what happens in the data, it is you the researcher that is interpreting it.
As you get better you while find more things in data that are significant.
As you learn more programs, the programs take you to greater abilities to interpret data.

5. Lets find the percent of poverty that is latin, 18-24, male /female etc. then percent of poverty that is black, 18-24 male/female. See example.
I find it easier to calculate in the other layout, before we transposed.
I calculated it horizontal but then transposed it so you can see it.
Now that’s all of the data. I made simple percents, you can use the other whole numbers to find things that may be more significant.

Step 2
1. Lets make a line graph making fair comparisons of our percents of no diplomas to the different percents we created.
It is better to compare them 1 at a time, like percent 18-24 with no diploma to latin male 18-24 no diploma etc.
If you sort the no diploma’s in order then as the line increases the comparative line will as well if there is a strong correlation.
If it doesn’t then there is little correlation, most things are in between.
Lets make 5 different line graphs. See the example of 1.

Step 3
1. Bullet points. Lets make 3 bullet points per line graph making a total of 15

Step 4
a. Paragraph of methods
b. Table that has been customized to your standards
c. 5 line graphs
d. 15 bullet points

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