Statistical Analysis & Explaination
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- Proposals: 11
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- #1567000
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Statistical Analysis using, R, Excel or SPSS, R programming, Latex Typesetting,
Iligan City
144073281422314150976493100775610409811193744141971116069731611056128388
Description
Experience Level: Intermediate
I need some exploratory data analysis; descriptive, regression, logistic, crosstabs, ANOVA, t-tests, anything that could find significance (if there is any) in my data. I have a general idea of my hypothesis, but I really am reverse engineering this. I want to know what is in my data and then determine my hypothesis... I know it is not exactly following the scientific method, but I am crunched for time.
My research idea is that a well's presence effects socioeconomic conditions in neighboring communities...
• H0 (the Null Hypothesis): IHFW sites do not effect the socioeconomic conditions of neighboring communities.
• H1 (the Alternative Hypothesis): IHFW sites effect the socioeconomic conditions of neighboring communities negatively.
Thus, Well Presence = Function of (Poverty, Household Income, Education Attainment, Unemployment). I also have other demographic values such as race and age.
However, I am not bound to this model if the data leads me elsewhere.
I have a 16 datasets: four datasets (inside 0.5 mile, inside 1.5 mile, outside 0.5 mile, and outside 1.5 mile buffers) of fracking well and socioeconomic data per year (1990, 2000, 2010, & 2014). Plus, I have a few aggregated datasets to be explored as well for t-Tests.
There is a short research paper I have included that did t-Tests in order to determine statistical significance of the differences between inside and outside buffers of 0.5 miles and 1.5 miles. Please look at it to get the gist of another approach I am considering.
Another issue is that I am pretty much stats illiterate and will need simple plain English explanations of what the columns in the results/outcome tables mean. Explain it to me like I am five years old.
Is this something you can help me with?
My research idea is that a well's presence effects socioeconomic conditions in neighboring communities...
• H0 (the Null Hypothesis): IHFW sites do not effect the socioeconomic conditions of neighboring communities.
• H1 (the Alternative Hypothesis): IHFW sites effect the socioeconomic conditions of neighboring communities negatively.
Thus, Well Presence = Function of (Poverty, Household Income, Education Attainment, Unemployment). I also have other demographic values such as race and age.
However, I am not bound to this model if the data leads me elsewhere.
I have a 16 datasets: four datasets (inside 0.5 mile, inside 1.5 mile, outside 0.5 mile, and outside 1.5 mile buffers) of fracking well and socioeconomic data per year (1990, 2000, 2010, & 2014). Plus, I have a few aggregated datasets to be explored as well for t-Tests.
There is a short research paper I have included that did t-Tests in order to determine statistical significance of the differences between inside and outside buffers of 0.5 miles and 1.5 miles. Please look at it to get the gist of another approach I am considering.
Another issue is that I am pretty much stats illiterate and will need simple plain English explanations of what the columns in the results/outcome tables mean. Explain it to me like I am five years old.
Is this something you can help me with?
Zachary J.
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Last project
21 Aug 2017
United States
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