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Producing Data, Randomization, and Experimental Design

Learn about observational studies versus experiments, design experiments using appropriate randomization, and understand new vocabulary words in the field of research.

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Producing Data, Randomization, and Experimental Design

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  1. Producing Data, Randomization, and Experimental Design

  2. Goals • Identify observational studies versus experiments • Design experiments to test hypotheses using appropriate randomization • Use the random number tables to assign subjects correctly to experimental groups • Define, use, and know the concepts behind all the new vocabulary words

  3. Starting with a research question • Often can’t simply study the whole population • If you want to know the life expectancy for cancer patients you simply can’t identify all patients and then wait for them to die • Use a sample to draw conclusions about the whole

  4. Observational Study vs. Experiment • Observational study observes and measures variables of interest. • Experiment imposes a treatment in order to observe outcome

  5. New Terminology • Population Sample • Voluntary response sample • Convenience sampling • Bias • Simple random sample (SRS)

  6. Use Random Numbers to Generate SRS • Label all the individuals in a population with numerical labels. • Use random number table (or statistical package) to choose individuals randomly. • Example: To divide 100 students into two groups of 50 label them 00 to 99 and go through the table starting at a random line until the first 50 have been chosen for a group.

  7. Other Sampling Designs • Probability sample • Individuals chosen with some given probability • Stratified random sample • Population divided into strata and individuals chosen at random from each strata • Multistage random sample • Sample chosen in a number of stages

  8. Problems • Undercoverage: some groups have no chance of being sampled; as in phone polling • Nonresponse: individuals chosen cannot or will not participate • Response bias: people may lie about illegal or embarrassing behavior; may respond to the questioner • Wording of questions may effect the outcome

  9. Designing Experiments • Experimental units or subjects • Treatment: experimental condition imposed • Factors: explanatory variables • Level: value of a given factor

  10. Example: Television ads

  11. Comparative Experiments • Compare 2 or more groups • Use a control group to eliminate confounding and placebo effect • A randomized comparative experiment uses comparisons between two (or more) groups and randomization of subjects into treatment groups.

  12. Design of a randomized comparative experiment

  13. Principles of Experimental Design • Control effects of lurking variables via comparison of several treatments • Randomization to assign units to treatment • Replication of experiment on many units to reduce chance variation

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