Introduction to Experimental Research

1. Introduction to Experimental Research Lawrence R. Gordon Psychology Research Methods I

2. From last class…Descriptive Stats • DISPLAYING DATA -- distributions, graphs,…”pictures” • Properties of distributions – symmetry, modality, skewness • Continuing today… • SUMMARIZING DATA – measures of central tendency & variability, …”numbers”

3. Descriptive Statistics • Name some you know of... • What can they do for us? • Tell us more about our data -- Location • Tell us more about our data -- Spread • Help us communicate these to others! • Highly summarized • Basis of results and tables in reports of studies

4. Measures of Central Tendency • Mode • the “typical” score • the peak(s) of the frequency distribution • Median • the “center” score • splits distribution into two halves (by area) • Mean • the (arithmetic) “average” of the scores • the balance point of the distribution (“seesaw”)

5. Central Tendency, contd. • Pros and Cons -- • Mode • Median • Mean • Relationships to distribution shapes -- • Symmetric: Mode = Median = Mean • Skewed: Pos (rgt)- Mo < Md < Mn Neg (lft)- Mn < Md < Mo

6. Variability • Range • Hi - Lo score • “Goes with” Mode • Interquartile range (IQR) • 75th-%ile - 25th-%ile scores • “Goes with” Median (50th-%ile score) • Standard Deviation (SD) • Sqrt of average of sqrd deviations around Mn • “Goes with” Mean [Handout for reference]

7. Real Data • First Hour Exam Scores

8. FIRST HOUR EXAM: Psyc 109, Fall 02 Exam I, 9/26/02 N Valid 234 Missing 1 Mean 37.9829 Median 38.0000 Mode 37.00 Std. Deviation 4.51128 Variance 20.35164 Range 24.00 Minimum 24.00 Maximum 48.00 25 Percentiles 35.0000 50 38.0000 41.0000 75

9. Real Data • Baseball salaries revisited

10. BASEBALL SALARIES 1994

11. Real Data • 109 Questionnaire - Scales (briefly!)

12. COURSE QUESTIONNAIRE CFC SCALE“Concern for Future Consequences” ScaleDescriptive Statistics

13. COURSE QUESTIONNAIRE: NC SCALE“Need for Cognition” ScaleDescriptive Statistics

14. Real Data • My dissertation data • A NOTE TO END ON: not everything interesting in data is captured by a single statistic! We must get to know data well, from many angles, to find its message! • NOW…on to our current topic, Experimental Research...

15. NOW, RESUMING… • Intro to Experimental Research, • A “pseudo-example”… • “Time flies when you’re having fun”! • DOES IT?

16. A Simple Experiment: “Time Flies” • EXAMPLE: “Time flies when you’re having fun” • Hypothesis: IF one is “having more fun”, THEN time will seem to pass more quickly • Design: • IV: 100 persons randomly assigned to two groups: • 1: “Having more fun” • 2: “Having less fun” • DV: Estimate of a standard 10 minute interval • Procedure: manipulation of cartoon captions

17. A Simple Experiment, cont. • EXAMPLE: “Time flies when you’re having fun” (cont..) • Results • “Raw data” • Organized by “frequency distribution” • Graphs of data • Group “dotplots” • Group histograms • Quickie summary of results: “More fun” group gave shorter estimates on average than “Less fun” group.

18. A Simple Experiment, cont. • RESULTS • How describe? • List of scores • A picture • A single number or two? • LOCATION = “central tendency” • SPREAD = “variability”

19. “Having Fun” Data

20. “HAVING FUN” DESCRIPTIVE STATISTICS: HISTOGRAMS W/ LEGENDS

21. “HAVING FUN” DESCRIPTIVE STATISTICS: TABLES 'More fun' (Captions) 'Less fun' (No Captions)

22. A Simple Experiment, cont. • Results (cont.) • Group 1 = “More fun” • Mean = 8.60, SD = 2.72, N = 50 • Group 2 = “Less fun” • Mean = 12.48, SD = 3.35, N = 50 • Quickie summary of results: the “More fun” group gave shorter estimates of the 10-minute interval, on average, than the “Less fun” group.

23. NOTE on the Mean & the SD • Most frequently used -- whenever possible • Often called “location” and “scale” -- why? • Examples of use with NORMAL curve (the “bell” curve) --- • Why used frequently? • Various commonly used “standard” scales • THAT’S ALL, FOLKS!