Chapter 13: Experiments and Observational Studies AP Statistics

Observational Studies Observational Studies: Researchers observe. They don’t assign choices or manipulate anything (unlike experiments). We just use an existing situation (or data), neither choosing who or what treatments. Example: A recent study showed that men who have had a heart attack, have a greater chance of having a second heart attack if a certain protein is present in their blood.

Observational Studies They are not based on random samples, nor do they randomly impose treatments. The results cannot be generalized, nor can they show cause- and-effect. They, however, are not worthless. They can show us trends and possible relationships—even if we can’t show cause-and- effect. They can show us variables related to certain outcomes

Types of Observational Studies Retrospective: Subjects are selected and then their previous conditions and behaviors are determined  restricted to small part of population  Prone to errors—looking at historical data  Usually focus on estimating differences between groups or associations between variables

Types of Observational Studies Prospective: Study where subjects are followed to observe future outcomes.  Focus is on estimating differences among groups that might appear as groups are followed  Because no treatment is applied, it is NOT and experiment.

Randomized, Comparative Experiments Only method by which we can prove cause-and- effect. We want to see if learning math on a computer is better than learning it in a traditional classroom—randomly assign half of a group of students to classroom where the content was only taught on computer and the other half to a classroom where the content was never taught on the computer, then we would compare the results.

Randomized, Comparative Experiments Comparative just means we are comparing the results at the end of the experiment.

Randomized, Comparative Experiments Also called a “factor” Each factor has levels—values that the experimenter chooses for the factors

Randomized, Comparative Experiments An experiment is designed to test the claim that those people who sleep less than 8 hours a night have a decreased ability to remember information. The experimenter has obtained 50 subjects and has randomly placed them in two groups. All subjects will be given a memory test as a baseline. One group will be required to sleep at least 8 hours for one night and the other groups will be prevented from sleeping 8 hours a night. The next day, each group will be given a test of memory and differences in the test will be recorded.

Randomized, Comparative Experiments Important Concepts The experimenter actively and deliberately manipulates the factors to control the details of the possible treatments. The subjects are assigned to the treatments randomly.

Four Principles of Experimental Design Control Randomization Replicate Block

Control We want to control sources of variation other than the factors we are testing by making conditions as similar as possible for all treatment groups. – We control a factor by assigning subjects to different factor levels because we want to see how the response will change at those different levels. – We control other sources of variation to prevent them from changing and affecting the response variable.

Control Controlling extraneous sources of variation reduces the variability of the responses, making it easier to detect differences among the treatment groups. Making generalizations from the experiment to other levels of the controlled factor can be risky.

Randomize Allows us to equalize the effects of unknown or uncontrollable sources of variation – Doesn’t eliminate those effect of these sources, but it spreads them out across all treatment levels, so that they “even out” and can be looked past. – If not randomized, you will not be able to draw conclusions from the experiment – “control what you can, randomize the rest”

Replicate 1 st type: We need to repeat the experiment, applying the treatment to a number of subjects. If we don’t assess the variation, it is not complete. The outcome of an experiment on a single subject is an anecdote—not an experiment

Replicate 2 nd type: Occurs when our experimental units (subjects) are not representative of the population of interest. We will need to repeat the experiment with a different experimental units. Replication of an entire experiment with the controlled sources of variation at different levels is an essential step in science. If your subjects are from an Intro to Psychology class, you can’t generalize the results—so you will need to replicate the experiment

Block Sometimes random assignment to treatments from our subjects is not the way to go. Sometimes we need to block. This is when we group experimental subjects that are known before the experiment to be similar in some way that is expected to affect the response to the treatments. The randomization comes within the blocks— where we assign treatments in each block

Logic to Experimental Design Randomization produces groups of subjects that should be similar in all respects before we apply treatments Comparative design ensures that influences other than the experimental treatment operate equally on all groups. Therefore, differences in the response variable must be due to the effects of the treatments

Experimental Diagram Diagram of a randomized comparative experiment. An experiment that was designed to test the effectiveness of the drug hydroxyurea for treating sickle cell anemia. There were 299 adult patients who had at least three episodes of pain from sickle cell anemia in the past year. The factor is: The response variable is: What are the treatments levels?

Experiment to test the effectiveness of see what treatment may reduce the number of repeat offenders.