ISDS 2000 Chapter : Chapter 7 Outline
15 Mar 2019
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Document Summary
Understand the reason for taking a sample as opposed to a census. Recognize that probability sampling is necessary when making statistical inferences. Know the definition of sampling and non-sampling error. Understand how sample size effects the sampling distribution. Example: nonsampling error (referred to as bias) error that results in a distortion of conclusions, nonresponse error/bias error incurred when some subjects refuse to respond to a survey. Example: estimating percentage of car crashes that involve alcohol. Drunk drivers usually refuse the bac test: coverage error (sometimes called selection bias) occurs when certain items are excluded from the sampling frame, measurement error (not intext) when data collected do not reflect the true measures. Example: cdc hepatitis survey, teacher evaluation requiring you to fill in your name, order of survey questions, etc: note: bias refers to the tendency of the sample statistic to systematically over- or under-estimate a population parameter. Types of samples selected based upon known probabilities.
