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Elements of Experimental Design

Elements of Experimental Design. Section 5.2 AP Statistics. Observational Study vs. Experiment. Observational study observes individuals and collects data, but does not try to influence them. Experiment deliberately imposes some treatment or behavior. Observational Studies-Examples.

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Elements of Experimental Design

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  1. Elements of Experimental Design Section 5.2 AP Statistics

  2. Observational Studyvs.Experiment • Observational study observes individuals and collects data, but does not try to influence them. • Experiment deliberately imposes some treatment or behavior.

  3. Observational Studies-Examples • Does adult smoking affect their children? • Do mal-nourished children have difficulties making friends? • Do people who do drugs sleep more than people who don’t?

  4. Experiments-Examples • Does aspirin make distance runners run faster? • Does the color purple attract the opposite sex?

  5. The importance of an experiment • Concluding that a cause and effect relationship exists between two variables is appropriate only when data comes from a well designed controlled experiment. • Data from an observational study can almost always be discounted on the basis of lurking variables and unintentional bias.

  6. Elements of an Experiment • Experimental Units: Subjects • Treatment: experimental condition applied to the subjects • Explanatory Variable: factor. Factors can be set at different levels • Response Variable: variable suspected to be changed by factor

  7. Control • An experiment should compare treatments allowing the only difference in groups to be the effect of the explanatory variable. • Try to make your treatment group and control group as similar as possible so that any changes seen in the two groups can be explained by explanatory variable.

  8. Designing an Experiment • 3 things you must have when designing an experiment. (pg. 361) • Control—comparison, blind, double blind • Randomization—assign units using chance • Replication—more experimental units reduces chance variation in the results.

  9. Outlining the design of an experiment Group 1 Compare results Experimental units Group 2 Response Variable Explanatory Variable

  10. An apple a day keeps the doctor away 30 eat apples # of doctor visits 60 volunteers 30 don’t eat apples Response Variable Experimental Units Explanatory Variable

  11. An apple a day keeps the doctor awayadding randomization Flip a coin to assign the participants to each group 30 eat apples # of doctor visits 60 volunteers Random allocation 30 don’t eat apples Response Variable Experimental Units Explanatory Variable

  12. Other Experimental Designs BLOCKING • This aspect of design occurs when the subjects are separated by some characteristic, and then the entire experiment is carried out on the groups separately. Blocking is stratifying within an experiment!

  13. Blocking-Example • You want to study the effect of cancer therapy on people. Since men and women may respond differently you block on gender separately, and conduct two separate experiments on the different blocks (each block will have its own control and experimental groups).

  14. Example 5.20 pg 367 Randomized Block Design

  15. Matching • Matching is often called matched pairs. • This is where you match subjects by type, then have one be in the control group and one be in the experimental group

  16. Matched Pairs-Example Let’s say you were going to test a new dog food. • You could minimize bias by pairing dogs of the same characteristics together, then placing one in the control group and one in the experimental group.

  17. Individual Matched Pairs • Because variation exists between different subjects this experimental design blocks a subject with himself/herself. • Each subject gets both treatments one after the other. • Each subject serves as his/her own control. • The order of the treatment is randomized.

  18. Beware! The Placebo Effect • Many subjects respond favorably to any treatment, presumably because of trust in the doctor and expectations of a cure. • Control lurking variables by including a control group that is given a placebo treatment.

  19. More Control • Blind Experiment—the subjects do not know if they are in the treatment group or the control group • Double Blind Experiment—both the subjects and the researchers are unaware of who receives treatments

  20. Reducing Bias With Randomization • After you have controlled for every kind of bias that you can think of use randomization to assign your experimental units to the control group and the treatment groups • Flip a coin • Use the random digit table • Use the random number generator on your calc

  21. Experimental Design Diagrams 5.27 & 5.31 (pg. 268 & 274) • Experimental units are the package liners • Factor (explanatory variable) is temperature • Response variable is force required to pull liners apart Group 1, 5 units  250ºF Group 2, 5 units  275ºF Measure force to open Package liners Group 3, 5 units  300ºF Random allocation Group 4, 5 units  325ºF Explanatory Variable Experimental Units Response Variable

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