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Introduction to Statistics for the Social Sciences SBS200, COMM200, GEOG200, PA200, POL200, or SOC200 Lecture Section 001, Fall, 2013 Room 120 Integrated Learning Center (ILC) 10:00 - 10:50 Mondays, Wednesdays & Fridays . Welcome. http://www.youtube.com/watch?v=oSQJP40PcGI.

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Welcome

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  1. Introduction to Statistics for the Social SciencesSBS200, COMM200, GEOG200, PA200, POL200, or SOC200Lecture Section 001, Fall, 2013Room 120 Integrated Learning Center (ILC)10:00 - 10:50 Mondays, Wednesdays & Fridays. Welcome http://www.youtube.com/watch?v=oSQJP40PcGI

  2. In nearly every class we will use clickers to: • answer questions in class and participate in • interactive class demonstrations • We’ll register them on our webpage- then use ‘em! student.turningtechnologies.com (Please note there is no “www”) Complete this in the next two weeks and receive extra credit! (By September 6th 2013)

  3. Please click in My last name starts with a letter somewhere between A. A – D B. E – L C. M – R D. S – Z

  4. Schedule of readings Before next exam (September 27th) Please read chapters 1 - 4 in Ha & Ha textbook Please read Appendix D, E & F onlineOn 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. Use this as your study guide By the end of lecture today9/4/13 Independent and dependent variables Control versus treatment True experimental versus quasi-experimental methodology Single blind (placebo) procedure Double blind procedure Continuous vs Discrete Variables Levels of Measurement Nominal, Ordinal, Interval, & Ratio Descriptive vsinferential

  6. Homework due – Friday (September 6th) On class website: please print and complete homework worksheet #2 Please double check – Allcell phones other electronic devices are turned off and stowed away

  7. Notetakers Name Major email phone #

  8. Lab sessions Everyone will want to be enrolled in one of the lab sessions No labs this week We will start week of September 9th

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

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

  11. Hiram S. Dudson 1930 – 1993Member ,Placebo Group

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

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

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

  15. Categorical versus 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

  16. 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 Handedness - right handed or left handed Family size Hair color Ethnic group GPA Age Yearly salary Breed of dog Gender - male or female Temperature Please note this is a binary variable

  17. 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 On a the top half of a writing assignment form please generate two examples of categorical data and two examples of numerical data Please note we’ll use the bottom half for something else

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

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

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

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

  22. Thank you! See you next time!!

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