1. Sampling Basics 2011, 9, 13

2. Last Class: Measurement  Scale of measurement –Nominal scale –Ordinal scale –Interval-ratio scale  Reliability: Free of random error –Test-retest reliability –Inter-rater reliability –Internal consistency  Validity: –Free of random error –Free of systematic bias –Measures what it is designed to measure

3. Reliability  An indication of the consistency or stability of a measuring instrument –Test-retest reliability: consistency from time to time –Inter-rater reliability: consistency from rater to rater –Internal consistency: consistency from item to item

4. Personality Test Disagree Disagree Neither agree Agree Agree strongly a little nor disagree a little strongly strongly a little nor disagree a little strongly 1 2 3 45 1 2 3 45 I see myself as someone who… 12345 1.is talkative. 2.is full of energy. 3.generates a lot of enthusiasm. 4.has an assertive personality. 5.is outgoing, sociable. 6.likes to make a lot of friends.

5. Lecture 3 Topics  Population and sample*  Sampling errors**

7. Population and Sample  Population –Everybody that the research is targeted –Population results: Population parameters  Sample –The subset of the population that actually participates in the research – make data collection manageable –Sample results: Sample statistics

9. A Population (N = 25); Population Parameter

10. Samples (n=6); Sample Statistics Sampling Variability: Random errors result from the differences among samples

11. Solution: Using a large sample – a large sample will have smaller variability since it represents the population better Samples (n=15); Sample Statistics

12. Sampling Error  The discrepancy between the population parameter and the sample statistic –Sampling variability

13. Solution: Using a random sample Sampling Bias: Systematic difference results from your method of choosing the sample

14. Sampling Error  The discrepancy between the population parameter and the sample statistic –Sampling variability –Sampling bias

15. Lecture Recap  Population and sample* –Population parameter –Sample statistic  Sampling Error** –Variability –Bias