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SAS Assignment 2: Applying what we have learned In this SAS assignment, you will go out and search for some public health data. You can get data in an excel form or transpose it to excel in any number...

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SAS Assignment 2: Applying what we have learned
In this SAS assignment, you will go out and search for some public health data. You can get data in an excel form or transpose it to excel in any number of ways (recommended). Also, this does not have to be patient specific information. You can get data on your local community (California) for the purpose of comparing and contrasting different values and categories.
To complete this assignment you will have to do the following:
Find a public health source of data. The data MUST have at least 4 columns information. Two of the columns should be categorical. If you find only continuous data then you can change age (a continuous variable) into discrete 10-year categories to aid in your analysis. 
Fun the following SAS procedures:
· PROC Contents (Add copy or screenshot)
· PROC FREQ (With tables and a Chi-Square) (Add copy or screenshot)
· PROC MEANS (Add copy or screenshot)
You will need to answer the following questions in minimum 500 words, APA style and references:
· What was the source?
· What conclusions can we draw from the basic statistics that were run?
· How does this compare with the research in the field?
Sources of Public Health Data:
CDC Sources
CDC WONDER: Mortality Data, Data on HIV/AIDS, Birth Statistics, Cancer Statistics,  Heat Index, Precipitation, Air Pollution etc
VAERS: Vaccine Adverse events
BRFSS: Behavioral Risk Factor Surveillance System
YBRFSS: Youth Risk Factor Surveillance System
California Specific Data
Cal-Enviroscreen 3.0: Air pollution, water contaminants, and toxic sites merged with asthma hospitalizations and death data
Disadvantaged Communities Map
Almost any source of data can be used, the goal of this activity is to start to get you to think of how to look at public health data and how it is organized on the back end.
Answered 2 days After Mar 06, 2022

Solution

Subhi answered on Mar 06 2022
108 Votes
· PROC Contents (Add copy or screenshot)
Proc content command gives us the information about our variables in the dataset. In our data set we had used five variables among with all of them were numeric type and with length of numeric as 8.
· PROC FREQ (With tables and a Chi-Square) (Add copy or screenshot)
A total sample of 2149 adults were interviewed in the survey among which 59.22% were overweight,11% were told by the doctor that they are diabetic,56% were female and 44% were male.
A chi square test was also run to see that is there any statistically significance between obese and diabetic.
Null Hypothesis: There is no association between obesity and diabetic.
Alternative Hypothesis: There is an association between obesity and diabetic.
The "chi-square statistic" has a value of 440.59 in our situation. In the "Asymptotic Significance (2-sided)" column, the p-value (0.0001) occurs in the same row. If this number is more than the prescribed alpha threshold, the result is statistically insignificant (usually .05).
Hence, there is enough evidence to claim that obesity and diabetic are significantly associated with each other, because the p-value is higher than the average alpha value in this situation, we reject the null hypothesis that the two variables are unrelated. To put it another way, the conclusion is essential - the data indicates that the variables obesity and diabetes are linked.
· PROC MEANS (Add copy or screenshot)
Proc means command was run over variable BMI_p (BMI) and the output conclude that the mean BMI...
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