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Research Design

Research Design. 10/16/2012. Readings. Chapter 3 Proposing Explanations, Framing Hypotheses, and Making Comparisons ( pp. 58-76) Chapter 5 Making Controlled Comparisons C hapter 4 Making Comparisons (Pollock Workbook ). Homework. Short homework assignment on the paper due today.

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Research Design

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  1. Research Design 10/16/2012

  2. Readings • Chapter 3 Proposing Explanations, Framing Hypotheses, and Making Comparisons (pp. 58-76) • Chapter 5 Making Controlled Comparisons • Chapter 4 Making Comparisons (Pollock Workbook)

  3. Homework • Short homework assignment on the paper due today Time Series Data

  4. Opportunities to discuss course content

  5. Office Hours For the Week • When • Wednesday 11-1 • Thursday 11-12 • Friday 10-11 • And appointment

  6. Course Learning Objectives • Students will learn the research methods commonly used in behavioral sciences and will be able to interpret and explain empirical data. • Students will learn the basics of research design and be able to critically analyze the advantages and disadvantages of different types of design.

  7. Research Design

  8. Types of Observational Studies • Cross-Sectional • Time-Series • Panel Studies

  9. Case Study Design • What is it? • N=1 (one unit in your study) • Problems

  10. Bivariate Data Analysis CROSS-TABULATIONS

  11. Variables • Dependent Variable- the variable/result that you want to explain. • Independent Variable(s)- the variables that you believe will cause/explain/change your dependent variable

  12. UnivariateStatistics answer discrete questions

  13. What are Cross Tabs? • a simple and effective way to measure relationships between two variables. • also called contingency tables- because it helps us look at whether the value of one variable is "contingent" upon that of another

  14. When to use them • When you have 2 variables • They can only be used for categorical variables • ordinal (variables are ranked, but the differences between them are not certain (Less than HS, Hs, College, Grad School), • nominal variables (the variables are simply given names Gingrich, Perry, Romney, Santorum)

  15. You can use them if you have • two ordinal variables • one nominal and one ordinal variable • two nominal variables. • Your variable can take less than 10 categories

  16. When it is a bad method • If you have ratio or interval variables • You have a variable with more than 10 values • You want to test multiple independent variables against a single d.v.

  17. Useless

  18. Doing cross-tabs in SPSS

  19. Open Up the GSS • Open GSS2008

  20. A Simple Hypothesis

  21. What is it • Dependent variable- Happiness • Independent variable- Intelligence • What would be the hypothesis

  22. Running Cross Tabs • Select, Analyze • Descriptive Statistics • Cross Tabulations

  23. Running Cross-Tabs We have to use the measures available • Dependent variable is usually the row • Independent variable is usually the column.

  24. Case Processing Summary • Ignore the case Processing Summary • Delete it from your outputs

  25. Cross-Tab Terminology • Rows (appear along the side of the table) and Columns (appear at the top) • the categories formed by the intersection of a column is called a cell

  26. The Outputs • As “Education increases, unhappiness increases” • Raw Counts are not very helpful Most are “pretty happy”

  27. Lets Add Some Percent's Click on Cells Cell Display

  28. Row %'s- This measures data across the row • 15% of people who are very happy have >11 years of education • Overall 27.7% have 16+ and 17.5% are less than 12. • This allows us to measure change across one category and compare to the total

  29. Column %'s This measures data down each column • Compare across each column • 37.0% of 16+ are very happy vs 27.0% of >11’s • 6.5 of 16+ are not too happy, vs 23.3% of people with low education • Overall, 31.6% of people are very happy

  30. How we interpret • Using Face Validity to interpret x-tabs • is there a pattern? • does one column stand out? • When we have two ordinal variables we can state directional relationships!

  31. The Compare means test

  32. When do we use this? • A way to compare ratio variables by controlling for an ordinal or nominal variable • One ordinal vs. a ratio or interval • One nominal vs. a ratio or interval • This shows the average of each category

  33. In SPSS • Open the States.SAV • Analyze • Compare Means • Means

  34. Where the Stuff Goes • Your categorical variable goes in the independent List • Your continuous variable goes in the Dependent List

  35. Reading the Output • We can compare each region against each other and the total • For ordinal variables, we can state relationships • This is all face validity!

  36. The Practical Significance • Why do some regions smoke more? (possible i.v.’s) • What are the policy effects? • Is smoking harmless?

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