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Understanding Observational Studies, Experiments, and Simple Random Sampling

This lesson covers the fundamental differences between observational studies and experiments, providing insight into how researchers use these methods to gather data. Key vocabulary terms such as census, frame, observational study, designed experiment, lurking variables, and simple random sample are defined. The lesson further explores four sources of data and various sampling techniques including simple random sampling, stratified sampling, cluster sampling, and systematic sampling. Understanding these concepts is crucial for accurate data collection and analysis in research.

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Understanding Observational Studies, Experiments, and Simple Random Sampling

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Presentation Transcript

  1. Lesson 1 - 2 Observational Studies, Experiments, and Simple Random Sampling

  2. Objectives • Distinguish between an observational study and an experiment • Obtain a simple random sample

  3. Vocabulary • Census – list of all individuals in a population along with certain characteristics • Frame – a list of all individuals in a population • Observational Study – measures the characteristics of a population by studying individuals in a sample; but does not try to influence the variable(s) of interest • Designed Experiment – applies a treatment to individuals (experimental units or subjects) and attempts to isolate the effects of the treatment on a response variable • Lurking variables – variables not identified in the study, but may be effecting the response variable • Simple random sample – every possible sample of size n has an equally likely chance of being selected from a population of size N

  4. Four sources of data • Census • Existing sources • Survey sampling • Designed experiments

  5. Four basic sampling techniques • Simple random sampling (SRS) • Stratified sampling • Some of all • Cluster sampling • All of some • Systematic sampling

  6. Summary and Homework • Summary • Homework • pg 19 – 21; 9-18, 20, 21

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