2. Introduction to Statistics for the Social Sciences SBS200, COMM200, GEOG200, PA200, POL200, or SOC200 Lecture Section 001, Fall, 2014 Room 120 Integrated Learning Center (ILC) 10:00 - 10:50 Mondays, Wednesdays & Fridays. http://www.youtube.com/watch?v=oSQJP40PcGI

3. Everyone will want to be enrolled in one of the lab sessions Labs will start on Monday

4. Schedule of readings Before next exam (September 26 th ) Please read chapters 1 - 4 in Ha & Ha textbook Please read Appendix D, E & F online On syllabus this is referred to as online readings 1, 2 & 3 Please read Chapters 1, 5, 6 and 13 in Plous Chapter 1: Selective Perception Chapter 5: Plasticity Chapter 6: Effects of Question Wording and Framing Chapter 13: Anchoring and Adjustment

5. Remember bring your writing assignment forms notebook and clickers to each lecture Talking or whispering to your neighbor can be a problem for us – please consider writing short notes. Complete this soon and receive extra credit! (By September 5th 2014) A note on doodling

7. By the end of lecture today 9/3/14 Use this as your study guide Constructs versus measurement Operational definitions Validity of operational definitions Reliability of measurements Independent and dependent variables Control versus treatment True experimental versus quasi-experimental methodology

8. Homework due – Friday (September 5 th ) On class website: please print and complete homework worksheet #2

9. Measurement: observable actions Theoretical constructs: concepts (like “humor” or “satisfaction”) So far, Operational definitions Validity and reliability Independent and dependent variable Random assignment and Random sampling Within-participant and between-participant design

10. If you want to know if studying improves test performance in young children Break up group of kids into two groups Group 1 - studies & tested Group 2 - does not study & tested What is the independent variable? Is this a “quasi” or “true” experiment? “Between” or “within” participant design? How many levels are there of the IV? What is the dependent variable? Review

11. If you want to know if “Ginseng drink” is associated with feelings of satisfaction What is the independent variable? “Between” or “within” participant design? What is the dependent variable? First test group with placebo drink (sugar pill) Then test same group with “Ginseng drink” Placebo How many levels are there of the IV? Review

17. Placebo (single blind) versus double blind procedure Single blind procedure (example: use of placebo) Double blind procedure What about experimenter bias?

18. Continuous versus discrete Continuous variable: Variables that can assume any value. There are (in principle) an infinite number of values between any two numbers Duration Distance Number of kids Height Discrete variable: Variables that can only assume whole numbers. There are no intermediate values between the whole numbers Number of eggs in a carton Number of textbooks required for class

19. Categorical data (also called qualitative data) - a set of observations where any single observation is a word or a number that represents a class or category Categorical versus Numerical data Numerical data (also called quantitative data) - a set of observations where any single observation is a number that represents an amount or count

20. Gender - male or female Handedness - right handed or left handed Family size Ethnic group Temperature Age Yearly salary Hair color GPA Breed of dog Categorical data (also called qualitative data) - a set of observations where any single observation is a word or a number that represents a class or category Numerical data (also called quantitative data) - a set of observations where any single observation is a number that represents an amount or count Please note this is a binary variable

21. On a the top half of a writing assignment form please generate two examples of categorical data and two examples of numerical data Categorical data (also called qualitative data) - a set of observations where any single observation is a word or a number that represents a class or category Numerical data (also called quantitative data) - a set of observations where any single observation is a number that represents an amount or count Please note we’ll use the bottom half for something else

22. What are the four “levels of measurement”? Interval data - measurable differences in amount, equal intervals Ordinal data - order, rankings, differences in degree Ratio data - measurable differences in amount with a “true zero” Categorical data Numerical data Nominal data - classification, differences in kind, names of categories

23. What are the four “levels of measurement”? Interval data - measurable differences in amount, equal intervals Ordinal data - order, rankings, differences in degree Ratio data - measurable differences in amount with a “true zero” Nominal data - classification, differences in kind, names of categories Gender - male or female Handedness - right handed or left handed Family size Jersey number Place in a foot race (1 st, 2 nd, 3 rd, etc) Categorical data Numerical data

24. What are the four “levels of measurement”? Interval data - measurable differences in amount, equal intervals Ordinal data - order, rankings, differences in degree Ratio data - measurable differences in amount with a “true zero” Nominal data - classification, differences in kind, names of categories Ethnic group Temperature Age Yearly salary Hair color Breed of dog Telephone number Categorical data Numerical data

26. What are the four “levels of measurement”? Interval data - measurable differences in amount, equal intervals Ordinal data - order, rankings, differences in degree Ratio data - measurable differences in amount with a “true zero” Look at your examples of qualitative and quantitative data. Which levels of measurement are they? Nominal data - classification, differences in kind, names of categories Categorical data Numerical data