1. Variables and Hypotheses 8/29/2013

2. Readings Chapter 1 The Measurement of Concepts (14- 23) (Pollock) Chapter 2 Measuring and Describing Variables (Pollock) (pp.28-31)

3. Backing Up Your Data Save the Information from the CD onto another media – Flash Drive – Edshare These are just data files, not a program

4. We Will Use the Full Version

5. Make Sure you move these files

6. The Files that We Will use Data Files on the Pollack CD GSS2008.SAV- the 2008 General Social Survey Dataset – n=2023 – 301 variables NES2008.SAV- the National Election Study from 2008. n=2323 – 302 variables STATES.SAV- aggregate level data for the 50 States. N=50 – 82 Variables WORLD.SAV- aggregate level data for the nations of the world. n=191 – 69 Variables

7. OPPORTUNITIES TO DISCUSS COURSE CONTENT

8. Office Hours For the Week When – Friday 10-12 – Tuesday 8-12 – And by appointment Last day to change any class is friday

9. Course Learning Objectives 1.Students will learn the research methods commonly used in behavioral sciences and will be able to interpret and explain empirical data. 2.Students will learn the basics of research design and be able to critically analyze the advantages and disadvantages of different types of design.

10. CONCEPTS The First Steps in Measurement

11. Concepts The words we use to describe political and social phenomenon Conceptual Definition- States the concept in unambiguous terms The Operational Definition- setting your concept in a way that can be measured

12. THE SECOND STEP: VARIABLES Measurement

13. What are Variables These are simply measured concepts Giving a concept value is called operationalization Good variables take on all values of a concept Why variables are important

14. How We Operationalize Fancy Fancy canned tomatoes must have a drained weight not less than 66% of the capacity of the container U.S. Grade B or U.S. Extra Standard must have a drained weight of not less than 58% of the capacity of the container

15. Variable Measurement constants Dichotomous Variables The rest

16. Dichotomous Variables

17. The Dependent Variable The variable in a relationship you want to explain. The Y variable There is only one of these in a relationship It changes in response to an independent variable

18. The Independent variable Variables that that cause change in the dependent variable The (X) variable You may have more than 1 of these

19. The Relationship Between them

20. Telling the Difference between I.V.’s and the D.V.

21. Additive Relationships Explaining a Dependent variable with more than 1 independent variable is called an additive relationship! Most Social Science relationships involve many i.v.’s…. Why?

22. Causes of Cancer

23. Additive Relationships

24. Independent Variables at Play

25. Why the Decline?

26. Antecedent and Intervening Variables Antecedent Come before the independent variable Things like Demographics Intervening Come in-between the IV and the DV Temporal events

27. How they can influence relationships

28. A Spurious Relationship What antecedent variable might be at play?

29. Intervening Variable

30. UNITS OF ANALYSIS How we measure our Variables

31. Units of analysis The unit about which information is collected and that provides the basis of analysis Each member of a population is an element Why they are important?

32. Individual Unit Studying an individual case or example A single survey response People, congressmen, presidents, etc

33. Aggregate Data A collection of individual level units Often measured in percentages

34. Counts can distort

35. The Poor over Time

36. Immigration over time

37. Health Care Access

38. FALLACIES MADE WITH DATA

39. Ecological Fallacy this arises when an aggregate/ecological level phenomenon is used to make inferences at the individual level. Taking statewide data and applying to individuals Does everyone in MS go to church?church

40. An Example On Mr. Burns Wanting to bowl: "Call this an unfair generalization if you must, but old people are no good at everything." Moe the Bartender from the Simpsons

41. The Exception Fallacy taking one person's behavior, attributes, etc and applying it to an entire group Using 1 example to define group behavior

42. Perceptions in Europe

43. Examples from Texas Style

44. How We View Others

45. HYPOTHESES

46. What Is a Hypothesis An educated Guess These are explicit Statements They Try to explain a relationship But they are only tentative until tested

47. The Null Hypothesis The Statement of No Relationship What we want to disprove The Basic start of research H0H0

48. On Stating the Null “there is no relationship between the independent and dependent variable”

49. Correlative Hypothesis “there is a relationship between x and y” A very weak statement

50. Positive Hypothesis A directional hypothesis “as the independent variable increases, the dependent variable increases”

51. Positive Relationship

52. On Stating a Positive relationship: There is a positive relationship between my independent variable (how much I drank) and dependent variable (the better you look)

53. Negative Relationship/Hypothesis “As the independent variable increases, the dependent variable decreases” Also called an inverse hypothesis

54. Minimum Wage

55. On Stating a negative hypothesis: There is a negative (inverse) relationship between “beers drank” (independent) and “grade” (dependent variable)