1. Skewness and Curves 10/1/2013

2. Readings Chapter 2 Measuring and Describing Variables (Pollock) (pp.37-44) Chapter 6. Foundations of Statistical Inference (128-133) (Pollock) Chapter 3 Transforming Variables (Pollock Workbook)

3. OPPORTUNITIES TO DISCUSS COURSE CONTENT

4. Office Hours For the Week When – Wedesday10-12 – Thursday 8-12 – And by appointment

5. Homework Chapter 2 – Question 1: A, B, C, D, E – Question 2: B, D, E (this requires a printout) – Question 3: A, B, D – Question 5: A, B, C, D – Question 7: A, B, C, D – Question 8: A, B, C

6. Course Learning Objectives 1.Students will learn the basics of research design and be able to critically analyze the advantages and disadvantages of different types of design. 2.Students Will be able to interpret and explain empirical data.

7. MEASURES OF DISPERSION

8. The Normal/Bell Shaped curve Symmetrical around the mean It has 1 hump, it is located in the middle, so the mean, median, and mode are all the same!

9. Why we use the normal curve To determine skewness The Normal Distribution curve is the basis for hypothesis/significance testing

10. What is skewness? an asymmetrical distribution. Skewness is also a measure of symmetry, Most often, the median is used as a measure of central tendency when data sets are skewed.

11. A distribution is said to be skewed if the magnitude of (Skewness value/ St. Error of Skew) is greater than 2 (in absolute value)

12. World Urban Population

13. STATISTICAL SIGNIFICANCE

14. Testing Causality Statistical Significance Practical Significance

15. Statistical Significance A result is called statistically significant if it is unlikely to have occurred by chance You use these to establish parameters, so that you can state probability that a parameter falls within a specified range called the confidence interval (chance or not). Practical significance says if a variable is important or useful for real-world. Practical significance is putting statistics into words that people can use and understand.

16. Curves & Significance Testing

17. What this Tells us Roughly 68% of the scores in a sample fall within one standard deviation of the mean Roughly 95% of the scores fall 2 standard deviations from the mean (the exact # for 95% is 1.96 s.d) Roughly 99% of the scores in the sample fall within three standard deviations of the mean

18. A Practice Example Assuming a normal curve compute the age (value) – For someone who is +1 s.d, from the mean – what number is -1 s.d. from the mean With this is assumption of normality, what % of cases should roughly fall within this range (+/-1 S.D.) What about 2 Standard Deviations, what percent should fall in this range?

19. Life Expectancy in Latin America and Caribbean Compute the estimated values for Average Life Expectancy for +/- 2 standard deviations from the mean. With this is assumption of normality, what % of cases should fall within this range (+/-2 s.d).

20. If you find this amusing or annoying, you get the concept

21. STANDARD DEVIATION AND CHARTS IN SPSS

22. Standard Deviation (open GSS)

23. For Ratio Variables Step 1 Step 2 Step 3 Step 4

24. Testing for Skewness In the Descriptive CommandIn the Frequencies Command Click Here

25. Simple Bar Charts In SPSS OPEN GSS 2008 Analyze – Descriptive Statistics Frequencies

27. PRINTING OUTPUTS

28. SPSS Printing SPSS outputs can be very large Much of the information is useless Please be smart in printing outputs

29. Step 1: Change your settings Change from portrait to landscape

30. Step 2: Highlight only the output you want

31. Step 3: Click on “selected output” Step 4: Choose ok

32. Research Design

33. What is a Research Design It is a plan for researchplan It guides the researcher through all aspects of the study

34. What it Includes: Your Unit of Analysis Unit of Analysis What is it that you are trying to study? What kind of data will you need

35. What it includes: Variables The Variables – Dependent (only 1) – The Independent(s) (additive) How you intend to measure each (operational definitions)

36. What it Includes: Hypotheses What is your null hypotheses for each relationship. What are your alternate hypotheses (for each relationship) Make sure these hypothesis are “good”

37. What it includes: Statistical Analysis What statistics you plan to use And Why

38. The Goal of A Research Design is to create a study that can demonstrate causality

39. INTERNAL VALIDITY OF DESIGN Working for Causality

40. Internal Validity Setting up Research Designs Properly Having control over the experiment. Especially the independent variable. This can be threatened

41. Threat 1:History You cannot account for all previous knowledge and events You cannot control for all potential independent variablesvariables

42. An Example

43. Threat 2: Maturation We get older We get wiser We get tired (short term) These are natural changes

44. Threat 3: Experimental Mortality Participants leave the research study The world changes Those who remain, may not be like the target group

45. Threat 4: Selection Bias Choosing the wrong sample Picking Respondents to favor your results Picking Respondents Excluding cases or respondents that do not fit your goals Using volunteers!

46. Threat 5: Instrumentation A Bad Measure Changing a Measure to Fit your Needs

47. Threat 6: Design Contamination People intentionally or unintentionally act differently “Instrument Reactivity” We Guess the test, we share informationinformation

48. Hawthorne Effect

49. Which of these are Most Common? History Maturation Selection Contamination is the worst!