PSYC 2002 Lecture Notes - Lecture 7: Type I And Type Ii Errors, Statistical Hypothesis Testing, Null Hypothesis
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Samples and their populations: whe(cid:374) (cid:449)e do(cid:374)"t ha(cid:448)e a(cid:272)(cid:272)ess to a populatio(cid:374), (cid:449)e use sa(cid:373)ples. Samples are not uniformly identical with each other. Sampling risk: the sample might not reflect the population, you might not know that the sample is misleading, traditional methodologies might not work today. Inaccurate conclusions: making conclusions that is based on the misleading data. Increases the level of confidence in findings: reach accurate conclusions at a low cost. Types of sampling: random sampling, random number table. Would randomly go through numbers to select individuals. Ideal way to do things, but expensive and hard to implement: convenience sampling, volunteer sample. Selection bias: no attempt to randomize, may work okay for basic projects. Random sampling vs random assignment: random sampling: all participants have equal chance of being selected and assigned to a condition, random assignment: ensure validity. Each person is randomly assigned to a condition,
