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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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