Assignment 1 Part 2 PH Surveillance Systems


Assignment 2 : Data analysis design with secondary data. Submit assignment 2 no later than 3/25 Friday

(1)  Variables can be used in your data analysis:

Age, City, Zip Code, Gender, Race, Ethnicity, Patient Language, Diagnosis Description, Discharge Disposition, Hospital Name, Insurance, Deceased, Emergency Room, LOS, Year. The variable year are required in all data analysis. 

(2) From your first assignment, after understanding the characteristics and background of diabetic in Bronx NY. You should already have the ideas of the following questions: 

(a) What kind of significant issues (or problems) facing the diabetics in Bronx?

(b) What kind of related research questions you want to research on?

(c) From the data analysis, what kind of related answers you expect to find out? (accept or reject results)

(3) The 2nd assignment is using the above variables listed at (1): 

(a) To construct at least 2 research questions (significant issues or problems) facing the diabetics in Bronx.

(b)  In each of the research question, you have to pick at least 2 variables from (1) (it can be related to the issues you mentioned in your first assignment).

(c) The variable Year is required in all analysis. 

(4) You can start from constructing a hypothesis to guide your data analysis design.

(a) Elaborate why you pick these 2 research questions?

(b) why you pick these variables for each of the research questions?

(c) What are the relationship between these variables?

(d)  How are you going to use these variables in the data analysis? 

(e) What do you expect from the result of the data analysis?  For example: Different assumptions on different analysis results. Based on the hypothesis (accept or reject) the assumption.

Be creative and elaborate as detail as you can. ** Often using how, how many, how much, why, what, which etc. to guide your thought.

For example: in this data analysis you can focus on the following perspectives: from Descriptive questions, Comparative questions, Relationship-based Question, Predictive questions, or Interpretive questions


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