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An Overview of Research Design:  14. Process & Analyze the Data
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See Also:  An Overview of Methods
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See Also:  Research Design
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1.  Selecting a Topic:   Finding the topic is the first step in research design
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2.  Formulate the Thesis
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3.  Choose the Types of Analyses
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4.   Research & Write a Literature Review & Refine the Thesis
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5. Formulate Research Objectives ( ROs ) from the Types of Analysis ( TOA )
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6. Conceptualization of the topic
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7.  Choose the methodology / the Research Instrument
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8. Operationalization
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9.  Formulate the Data Collection Strategy
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10.    Obtain HIC Approval
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11.  Perform a Pilot Study:  the Senior Project is a Pilot Study & so no addition study will be required
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12.  Collect Data utilizing efficient, effective & ethical methodological practices
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13.  Prepare the Data for processing & analysis
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14.  Processing & Analyzing Data is determined by the type of data collected 
        by the Research Instruments in that Data Prepartionn is quite different for surveys & content analysis, etc.
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       Chi-squared:  must have discrete, 2-way variables
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Data must be able to be put into discrete, 2 way categories
Yes - No
Male - Female
Urban - Rural....
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Then the chi squared test may tell you two things:
A.  Is there is a significant difference btwn the two variables, or not?
B.  Is there a correlation btwn two variables, or not?
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A. Chi-sq can be used to determine whether there is a significant difference btwn 2 variables or not
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    Example:  Is there a significant difference in the male/female vote?
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    Is there is a significant difference btwn the two categories, or not?
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   Are the different answers given by men & women actually different, 
      or could random chance account for the difference?
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      Example:  Gender gap in Presidential politics
      40 % of Women voted for Bush
      60 % of Women voted for Gore
      60 % of Men voted for Bush
      40 % of Men voted for Gore
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      Given the sample #, & the differences in %,
         the Chi squared test will tell you whether W & M
         have a true difference in voter preference or whether this "gender gap"
         could have been the result of chance
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     Example:  Is there a significant difference in the in the intro/extroversion 
                     of sociology & business majors?
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      Correlation is the closest term we have to "cause"
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B.  Chi-sq can be used to determine whether  there a correlation btwn 2 variables or not?
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      See Also:  Correlation 
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      Example:  Is a flat org structure more efficient than a hierarchical org structure?
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      Example:  Does introversion/extroversion affect grades? 
                      of sociology & business majors?
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Is there a correlation btwn two variables, or not?
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     But must meet all the requirements
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          A occurs before B
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          When A occurs, B occurs... in a regular pattern
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          We must be sure that no intervening variable is causing A & B
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Example:  Is a flat org structure more efficient than a hierarchical org structure?
     Flat structure          37% efficient
     Flat structure          63% inefficient
     Hier structure          52 % efficient
     Hier structure          48 % inefficient
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The trend is obviously that the flat structure is more efficient,
   but a Chi sq test will tell us whether there is a correlation here,
   or whether the result is explainable by chance
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      See Also:  The Summary of the Results/Data in the Research Paper
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      See Also:  Analysis / Discussion Subsections in the Research Paper
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15.  Interpret & make Inferences about Data
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16.  Write the Final Report
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17.  Write Final HIC Report
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The End