Experiments

1. Experiments Section 4.2A

2. Observational Study • Observes individuals and measures variables of interest but does not attempt to influence the responses • Goal: • To describe some group or situation, to compare groups, or to examine relationships between variables.

3. Experiment • Deliberately imposes some treatment on individuals to measure their responses. • Goal: • To understand the response to a change

4. Does Taking Hormones Reduce Heart Attack Risk after Menopause? • Should women take hormones such as estrogen after menopause, when natural production of these hormones ends? In 1992, several major medical organizations said “yes.” Women who took hormones seemed to reduce their risk of a heart attack by 35% to 50%. The risks of taking hormones appeared small compared to the benefits. • This came from a number of observational studies that compared women who were taking hormones with others who were not. But the women who chose to take hormones were richer and better educated and saw doctors more often than women who didn’t take hormones. Because the women who took hormones did many other things to maintain their health, it isn’t surprising that they had fewer heart attacks. • After doing real experiments…they found that taking hormones did not reduce the risk of heart attacks. They are now out of favor.

5. Lurking Variables • A variable that is not among the explanatory or response variables in a study but that may influence the response variable. • Hormone Replacement Study • The effect of taking hormones was mixed up with the characteristics of women. These characteristics were lurking variables.

6. Confounding • This occurs when two variables are associated in such a way that their effects on a response variable cannot be distinguished from each other.

7. Example Professor wanted to see if his style had an effect on students in New York. He taught the fall & spring classes identically – same text, syllabus, etc. - but in the fall he used a subdued demeanor and in the spring he used expansive gestures & lectured with more enthusiasm.

8. The fall class rated him an average teacher. The spring class rated him excellent and praised him on everything. Can we conclude that the teacher’s style had a role in the students’ evaluations?

9. NO! Confounding variables Fall ends cold & bleak Spring is bright & cheerful. The student’s happiness could have been affected by the season & reflected in their evaluations.

10. Observational studies often fail because of confounding between the explanatory variable and one or more lurking variables.

11. Observational or Experimental • Does reducing screen brightness increase battery life in laptop computers? To find out, researchers obtained 30 new laptops of the same brand. They chose 15 of the computers at random and adjusted their screens to the brightest setting. The other 15 laptop screens were left at the default setting – moderate brightness. Researchers then measured how long each machine’s battery lasted. • Experiment – treatment was imposed.

12. Does eating dinner with their families improve students’ academic performance? According to an ABC News article, “Teenagers who eat with their families at least five times a week are more likely to get better grades in school.” This finding was based on a sample survey conducted by researchers at Columbia University. • Is this observational or experimental? • If observational, what are the lurking variables that may be confounded? • If experimental, what is the treatment? • What are the explanatory and response variables?

13. Factors • The explanatory variable…many experiments study the joint effects of several factors.

14. Treatment • A specific condition applied to the individuals in an experiment. • If more than one factor, then the treatment is a combination of specific values of these variables.

15. Experimental Units • The smallest collection of individuals to which treatments are applied. • When the units are human beings, they are often called subjects.

16. A study published in the New England Journal of Medicine (March 11, 2010) compared two medicines to treat head lice: an oral medication called ivermectin& a topical lotion containing malathion. Researchers studied 812 people in 376 households in seven areas around the world. Of the 185 randomly assigned to ivermectin, 171 were free from head lice after two weeks compared to only 151 of the 191 households randomly assigned to malathion. • Experimental Units • Explanatory Variable • Response Variable • Treatments

17. Does adding fertilizer affect the productivity of tomato plants? How about the amount of water given to the plants? To answer these questions, a gardener plants 24 similar tomato plants in identical pots in his greenhouse. He will add fertilizer to the soil in half of the pots. Also, he will water 8 of the plants with 0.5 gallons of water per day, 8 of the plants with 1 gallon of water per day and the remaining 8 plants with 1.5 gallons of water per day. At the end of three months he will record the total weight of tomatoes produced on each plant. • Experimental Units • Explanatory Variable • Response Variable • Treatments

18. Example: What’s the effect of repeated exposure to an ad? An experimenter used undergraduate students as subjects. All subjects viewed a 40 min. t.v program with ads for a camera. Some saw a 30-sec commercial – others a 90-sec commercial. It was shown either 1, 3, or 5 times during the program. Experimental Unit: Factors: Treatments:

19. 2 Factors: length of commercial #times it played 6 treatments Response: Subjects answer questions about their recall of the ad, their attitude toward the camera & intent to purchase.

20. Many students regularly consume caffeine to help them stay alert. Thus, it seems plausible that taking caffeine might increase an individual’s pulse rate. Is this true? One way to investigate this is to have volunteers measure their pulse rates, drink some cola with caffeine, measure their pulses again after 10 minutes and calculate the increase in pulse rate. • What is wrong with this study?

21. Good Experiments • Use a comparative design to compare two or more treatments. • Randomly assign experimental units to the treatments. • Be specific about how you are randomly placing them

22. Completely Randomized Design *All experimental units are allocated at random among all treatments. Ex: Does talking on a hands-free cell phone distract drivers?

23. Group 1 (20 students) Treatment 1 (Drive) Random allocation Compare brake time Group 2 (20 students) Treatment 2 (Drive & Talk) Put the 40 names in a hat, mix them up, and draw 20. This will form the experimental group and the remaining 20 will make up the control group.

24. A health organization wants to know if a low-carb or low-fat diet is more effective for long-term weight loss. The organization decides to conduct an experiment to compare these two diet plans with a control group that is only provided with brochure about healthy eating. Ninety volunteers agree to participate in the study for one year.

25. Principles of Experimental Design Control– the effects of lurking variables on the response, most simply by comparing two or more treatments. Replication – Apply treatment to a number of subjects& repeat the experiment. Randomization – Equalize the effects of un- known or uncontrollable sources of variation – used to assign treatments.

26. Example “Gastric Freezing” is used to treat ulcers in the upper intestine. Patient swallows a deflated balloon with tubes attached, then a refrigerated liquid is pumped through the balloon for an hour. This reduces the acid and relieves the pain. Design: Gastric freezing →Observed pain relief

27. Placebo – dummy treatment Placebo Effect– Respond favorable to any treatment, even a placebo. Control Group– The group of patients who receive the sham treatment.

28. Gastric Freezing Revisited • Used 2 groups • Control group used (fluid was room temp) • 34% of treatment group improved • 38% of control group improved They were not statistically different and thus gastric freezing has been abandoned.

29. Blinding * Single-blind – Subjects do not know what treatment they received (controls for personal beliefs) • Double-blind – neither the subject nor the individual measuring the response know which treat- ment was received.

30. Example Subjects were told the experiment was about 3-D spatial perception and were assigned to draw a model of a horse. While they were busy drawing, a loud noise and then groaning were heard coming from the room next door. The real purpose of the experiment was to see how people reacted to the apparent disaster.

32. Homework • Page 227 (37-42) • Page 253 ( 45, 47, 57, 65) • Worksheet