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Experimental Designs

Experimental Designs. Day 1: Randomized Comparative Design and the Energy Drink Experiment. What’s wrong with this experiment?.

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Experimental Designs

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  1. Experimental Designs Day 1: Randomized Comparative Design and the Energy Drink Experiment

  2. What’s wrong with this experiment? • We want to know if a nicotine patch helps smokers stop smoking so we take 100 smokers and make them wear the patch for 2 months and record how many cigarettes they now smoke. • Everyone is doing the same thing so you don’t have anything to compare it to. • Too many LURKING VARIABLES

  3. Diagram We need to eliminate the effects of lurking variables by using a control group. One track design Body Weight, Age, Gender Nicotine Patch # of Cigarettes Smoked ? ? ? Patch usage, support from peers Type of Smoker (Lurking variables)

  4. Why Do Experiments? • A well-designed experiment can rule out lurking variables by controlling the environment. • Only way to prove causation.

  5. 3 Principles of Experimental Design: • Control – one group gets no treatment, an old treatment, or a placebo (fake treatment) • Randomization – randomly put people into a group to remove bias • Replication - Large sample size reduces variability of results

  6. Good Experiments MAY include: • Placebo – a “fake” treatment meant to look like the real thing. Eliminates the placebo effect (reacting the way a subject thinks he/she should) • Single – blind – Subject doesn’t know what treatment is being given • Double-blind - BOTH the subject and the doctor/researcher don’t know what treatment is being given

  7. Powerful Placebos • 42% of balding men regrew hair after taking a placebo. • Poison Ivy Study – 13 people allergic to poison ivy • On one arm they were told they were rubbing poison ivy on them (even though it was really a placebo) and all 13 broke out in a rash. • On the other arm they were told they were rubbing a placebo on them (even though it was the real thing) and only 2 of them broke out in a rash. • When would it not be possible? • If you need a real treatment.

  8. Vocabulary • Experimental Units– individuals • Subjects – if units are human • Treatment – specific experimental condition applied to the units • Factors - explanatory variables • Level– specific value of a factor

  9. Randomized Comparative Experimental Design • Basic Design • Randomly Assign subjects into groups • Give a treatment (control, placebo, other) • Compare results

  10. Randomized Comparative Experiment Diagram Group 1 # of students Treatment 1 Control – No pop Random Assignment Group 2 # of students Treatment 2 Caffeine Free Compare Heart rates Group 3 # of students Treatment 3 Regular Pop

  11. Results • Statistically significant means the observed effect was SO LARGE that it would rarely occur by chance.

  12. Was ours a good experiment? • Control Group • Randomizaton • Replication • Placebo • Blind

  13. Homework • Pg 293-299 #31-34,36-37,39(on part b only find first 5),40,42

  14. Lots of treatments… • For example if you want to test how long your clothes last after being washed several times, but you want to know if the laundry detergent and the temperature of the water affects it. • Set up a matrix.

  15. Completely Random Design Matrix Design – Detergent/Temp Example Randomly Assign Compare fabric durability

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