Sampling Basics 2011, 9, 13
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
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
Personality Test Disagree Disagree Neither agree Agree Agree strongly a little nor disagree a little strongly strongly a little nor disagree a little strongly I see myself as someone who… 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.
Lecture 3 Topics Population and sample* Sampling errors**
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
A Population (N = 25); Population Parameter
Samples (n=6); Sample Statistics Sampling Variability: Random errors result from the differences among samples
Solution: Using a large sample – a large sample will have smaller variability since it represents the population better Samples (n=15); Sample Statistics
Sampling Error The discrepancy between the population parameter and the sample statistic –Sampling variability
Solution: Using a random sample Sampling Bias: Systematic difference results from your method of choosing the sample
Sampling Error The discrepancy between the population parameter and the sample statistic –Sampling variability –Sampling bias
Lecture Recap Population and sample* –Population parameter –Sample statistic Sampling Error** –Variability –Bias