2. Modern Languages 14131211109 87 6 54321 111098765 43 2 Row A Row B Row C Row D Row E Row F Row G Row H Row J Row K Row L Row M 212019181716 1514 13 12111098 212019181716 13 12111098 141312 table 7 6 54321 Row C Row D Row E Row F Row G Row H Row J Row K Row L Row M 321 21 1413 Projection Booth 212019181716 1514 13 12111098 212019181716 1514 13 12111098 212019181716 1514 13 12111098 212019181716 1514 13 12111098 212019181716 1514 13 12111098 212019181716 1514 13 12111098 212019181716 1514 13 12111098 212019181716 1514 13 12111098 7 6 5432 1 765 43 2 1 7 6 5432 1 765 43 2 1 7 6 54321 765 43 2 1 7 6 54321 765 43 2 1 7 6 54321 table Row C Row D Row E Row F Row G Row H Row J Row K Row L Row M 321 28 27 26252423 22 282726 2524 23 22 282726 2524 23 22 28 27 26252423 22 282726 2524 23 22 282726 2524 23 22 28 27 26252423 22 282726 2524 23 22 282726 2524 23 22 282726 2524 23 22 R/L handed broken desk Stage Lecturer’s desk Screen 1

3. MGMT 276: Statistical Inference in Management Spring 2015

4. By the end of lecture today 1/27/15 Use this as your study guide Single versus Double Blind Studies Nominal, Ordinal, Interval, Ratio Categorical vs Numerical (Quantitative vs Qualitative) Field observation/naturalistic research Time series design vs. Cross sectional design Descriptive versus inferential analyses

5. Talking or whispering to your neighbor can be a problem for us – please consider writing short notes. Complete this in the next two weeks and receive extra credit! (By February 3rd 2015) A note on doodling Remember bring your writing assignment forms notebook and clickers to each lecture

7. Homework due- (Thursday, January 29 th ) On class website: please print and complete homework worksheet #1

8. Schedule of readings Before next exam: February 17 th Please read chapters 1 - 4 & Appendix D & E in Lind 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

9. 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

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

11. 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 Single blind (placebo) and double blind procedures

12. Duration Distance to the moon Number of kids in classroom Height Number of eggs in a carton Number of textbooks required for class Amount of sand Grains of sand Number of cookies on a plate Amount of milk in a glass 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 two nearest values

13. 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

14. Gender - male or female Handedness - right handed or left handed Family size Ethnic group Temperature (Fahrenheit) Age (Time since birth) 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 Temperature (Kelvin)

15. 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

16. What are the four “levels of measurement”? Nominal Ordinal Interval Ratio Names Categories Least numeric Weakest Names Categories Intrinsic ordering Approaching Numeric Categories Intrinsic ordering Equal sized intervals Units meaningful Most numeric Absolute zero

17. 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

18. 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

19. Please note : page 29 in text

20. 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

22. Descriptive statistics - organizing and summarizing data Descriptive or inferential? Inferential statistics - generalizing beyond actual observations making “inferences” based on data collected What is the average height of the basketball team? In this class, percentage of students who support the death penalty? Based on the data collected from the students in this class we can conclude that 60% of the students at this university support the death penalty Measured all of the players and reported the average height Measured all of the students in class and reported percentage who said “yes” Measured only a sample of the players and reported the average height for team Measured only a sample of the students in class and reported percentage who said “yes”

23. Descriptive statistics - organizing and summarizing data Descriptive or inferential? Inferential statistics - generalizing beyond actual observations making “inferences” based on data collected Men are in general taller than women Shoe size is not a good predictor of intelligence Blondes have more fun The average age of students at the U of A is 21 Measured all of the citizens of Arizona and reported heights Measured all of the shoe sizes and IQ of students of 20 universities Asked 500 actresses to complete a happiness survey Asked all students in the fraternities and sororities their age

24. Descriptive statistics - organizing and summarizing data Descriptive vs inferential statistics Inferential statistics - generalizing beyond actual observations making “inferences” based on data collected To determine this we have to consider the methodologies used in collecting the data

25. Time series versus cross-sectional comparisons: Trends over time versus a snapshot comparison Trends over time versus a snapshot comparison Time series design: Each observation represents a measurement at some point in time. Repeated measurements allow us to see trends. Cross-sectional design: Each observation represents a measurement at some point in time. Comparing across groups allows us to see differences. Please note: Any one piece of data can often (not always) be used in either a time series comparison or a cross-sectional comparison. It depends how you set up your question. Traffic accidents Does Tucson or Albuquerque have more traffic accidents (they have similar population sizes)? Does Tucson have more traffic accidents as the year ends and winter approaches?

26. Time series versus cross-sectional comparisons: Trends over time versus a snapshot comparison Trends over time versus a snapshot comparison Time series design: Each observation represents a measurement at some point in time. Repeated measurements allow us to see trends. Cross-sectional design: Each observation represents a measurement at some point in time. Comparing across groups allows us to see differences. Unemployment rate Is there an increase in workers calling in sick as the summer months approach? Do more young workers call in sick than older workers? Grade point average (GPA) Does GPA tend to go up or down as students move from freshman to sophomores to juniors to seniors? Does GPA tend to go up or down when you compare Mr. Chen’s class with Mr. Frank’s Freshman English classes?

27. 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 Single blind (placebo) and double blind procedures

28. Continuous vs Discrete variables Quantitative vs qualitative variables So far, Levels of measurement: Nominal, Ordinal, Interval and Ratio Descriptive vs inferential statistics Time series versus cross-sectional comparisons:

29. Let’s try one A study explored whether eating carrots really improves vision. Half of the subjects ate a package of carrots everyday for 3 months while the other group did not. Then, they tested the vision for all of the subjects. The independent variable in this study was a. the performance of the subjects on the vision exam b. the subjects who ate the carrots c. whether or not the subjects ate the carrots d. whether or not the subjects had their vision tested

30. A study explored whether eating carrots really improves vision. Half of the subjects ate a package of carrots everyday for 3 months while the other group did not. Then, they tested the vision for all of the subjects. The dependent variable in this study was a. the performance of the subjects on the vision exam b. the subjects who ate the carrots c. whether or not the subjects ate the carrots d. whether or not the subjects had their vision tested Let’s try one

31. A study explored whether eating carrots really improves vision. Half of the subjects ate a package of carrots everyday for 3 months while the other group did not. Then, they tested the vision for all of the subjects. This experiment was a a. within participant experiment b. between participant experiment c. mixed participant experiment d. non-participant experiment Let’s try one

32. When Martiza was preparing her experiment, she knew it was important that the participants not know which condition they were in, to avoid bias from the subjects. This is called a _____ study. She also was careful that the experimenters who were interacting with the participants did not know which condition those participants were in. This is called a ____ study. a. between participant; within participant b. within participant; between participant c. double blind design; single blind d. single blind; double blind design Let’s try one

33. A measurement that has high validity is one that a. measures what it intends to measure b. will give you similar results with each replication c. will compare the performance of the same subjects in each experimental condition d. will compare the performance of different subjects in each experimental condition Let’s try one

34. A study explored whether conservatives or liberals had more bumper stickers on their cars. The researchers ask 100 activists to complete a conservative/liberal values test, then used those results to categorize them as liberal or conservative. Then they identified the 30 most conservative activists and the 30 most liberal activists and measured how many bumper stickers each activist had on their car. The independent variable in this study was a. the performance of the activists b. the number of bumper stickers found on their car c. political status of participant (liberal versus conservative) as determined by their performance on the liberal/conservative test d. whether or not the subjects had bumper stickers on their car Let’s try one

35. A study explored whether conservatives or liberals had more bumper stickers on their cars. The researchers asked 100 activists to complete a conservative/liberal values test, then used those results to categorize them as liberal or conservative. Then they identified the 30 most conservative activists and the 30 most liberal activists and measured how many bumper stickers each activist had on their car. The dependent variable in this study was a. the performance of the activists b. the number of bumper stickers found on their car c. political status of participant (liberal versus conservative) as determined by their performance on the liberal/conservative test d. whether or not the subjects had bumper stickers on their car Let’s try one

36. A study explored whether conservatives or liberals had more bumper stickers on their cars. The researchers 100 activists to complete a conservative/liberal values test, then used those results to categorize them as liberal or conservative. Then they identified the 30 most conservative activists and the 30 most liberal activists and measured how many bumper stickers each activist had on their car. This study was a a. within participant experiment b. between participant experiment c. mixed participant experiment d. non-participant experiment

37. Let’s try one A study explored whether conservatives or liberals had more bumper stickers on their cars. They had 100 activists complete liberal/conservative test. Then, they split the 100 activists into 2 groups (conservatives and liberals). They then measured how many bumper stickers each activist had on their car. This study used a a. true experimental design b. quasi-experiment design c. correlational design d. mixed design

38. Writing Assignment – Pop Quiz Section 1 completed this – Section 2 did not