1. Warm-Up Grab a sheet and review!

2. Section 4.2 Experiments Some of these things are going to look familiar, but remember…we are talking about different things! Surveys vs. Experiments!

3. Definitions An observational study observes individuals and measures variables of interest but does not attempt to influence the response. An experiment deliberately imposes some treatment on individuals to measure their responses. ◦ When our goal is to understand cause and effect, experiments are the only source of fully convincing data.

4. Lurking Variable A lurking variable is a variable that is not among the explanatory or response variables in a study but that may influence the response variable. Confounding occurs when two variables are associated in such a way that their effects on a response variable cannot be distinguished from each other.

5. Example Does taking hormones reduce heart attack risks in women after menopause? The evidence in favor of hormone replacement 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. Because they took steps to maintain better health, they had fewer heart attacks. The effect of taking hormones was mixed up with the characteristics of women who chose to take them, so these characteristics were lurking variables. The effects of the two variables (the hormones and the characteristics of the women) on a response variable (heart attacks) cannot be separated from each other so it is confounding.

6. The Language of Experiments A specific condition applied to the individuals in an experiment is called a treatment. If an experiment has several explanatory variables, a treatment is a combination of specific values of these variables. The experimental units are the smallest collection of individuals to which treatments are applied. When the units are human beings, they are often called subjects.

7. Identify the following: A study published in the New England Journal of Medicine compared two medicines to treat head lice: invermectin and malathion. Researchers studied 812 people in 376 households in seven areas around the world. Of the 185 households randomly assigned to ivermectin, 171 were free from head lice after two weeks compared with only 151 of the 191 households randomly assigned to malathion. Experimental units: Households (not people) Explanatory variable: Type of Medication Response Variable: Whether or not lice free Treatments: ivermectin and malathion

8. How to experiment well: In an experiment, random assignment means that the experimental units are assigned to treatments at random, that is, using some sort of chance process. Look at the SAT Prep example in your book on page 237 – notice figure 4.4 on page 238 for completely randomized design

9. Definition In a completely randomized design, the treatments are assigned to all the experimental units completely by chance. The example on page 239 walks through an experiment that compares three treatments.

10. Three principals of experimental design 1. Control for lurking variables that might affect the response. Use a comparative design and ensure that the only systematic difference between the groups is the treatment administered. 2. Random assignment: Use impersonal chance to assign experimental units to treatments. This helps create roughly equivalent groups of experimental units by balancing the effects of lurking variables that aren’t controlled on the treatment group. 3. Replication: Use enough experimental units in each group so that any differences in the effects of the treatments can be distinguished from chance differences between the groups.

11. What can go wrong? The response to a dummy treatment is called the placebo effect, in which some patients get better because they expect the treatment to work even though they have received an inactive treatment. Give me an example of what you might think this represents…

12. Going Blind! In a double-blind experiment, neither the subjects nor those who interact with them and measure the response variable know which treatment a subject received. Single-blind experiments occur when one party knows and the other doesn’t.

13. Definition An observed effect so large that it would rarely occur by chance is called statistically significant. A statistically significant association in data from a well-designed experiment does imply causation.

14. More Definitions A block is a group of experimental units that are known before the experiment to be similar in some way that is expected to affect the response to the treatments. ◦ Another form of control! In a randomized block design, the random assignment of experimental units to treatments is carried out separately within each block.

15. Example of blocking Doing laundry! Since researchers know that color may affect cleanliness in a systematic way, they could start by separating clothes into two piles – lighter colors and darker colors. Each of these piles is known as a block. Look at design on page 247

16. Matched Pairs Design A matched pairs design is a special case of a randomized block design that uses blocks of size 2. (Pairs!) ◦ In some, each subject receives both treatments in a random order. ◦ In others, the subjects are matched in pairs as closely as possible, and each subject in a pair receives on of the treatments.

17. Homework Pg. 253 (46, 48, 50-53, 60, 61, 68-70, 83, 91-98)