Chapter 4: Designing Studies

Size: px

Start display at page:

Download "Chapter 4: Designing Studies"

Moses Wilson
7 years ago
Views:

1 Chapter 4: Designing Studies Section 4.3 The Practice of Statistics, 4 th edition For AP* STARNES, YATES, MOORE

2 Chapter 4 Designing Studies 4.1 Samples and Surveys 4.2 Experiments 4.3

3 Section 4.3 Learning Objectives After this section, you should be able to DESCRIBE the challenges of establishing causation DEFINE the scope of inference DESCRIBE data ethics in designing studies

4 Scope of Inference What type of inference can be made from a particular study? The answer depends on the design of the study. Well-designed experiments randomly assign individuals to treatment groups. However, most experiments don t select experimental units at random from the larger population. That limits such experiments to inference about cause and effect. Observational studies don t randomly assign individuals to groups, which rules out inference about cause and effect. Observational studies that use random sampling can make inferences about the population.

5 Alterate Example Silence is Golden Many students insist that they study better when listening to music. A teacher doubts this claim and suspects that listening to music actually hurts academic performance. What can we conclude for each design? Get Select all a the random students sample in your of AP students Statistics from class your to school participate to participate in a study. in a study. Ask Randomly them Randomly Then whether divide assign assign them half or not of half into they of two students the study groups students with to as listen music in to Design listen to on music and to 1. music divide while them studying while into studying for two the groups for entire the based entire semester semester on their and answer have and the have to remaining this the question. remaining half abstain half from abstain With listening from random listen to music selection, to music while the while studying. results studying. of the study can be applied With to the no entire random population selection, in the this results case, of all the study students should in the be applied school. With no random only random With to selection, no the random AP Statistics the assignment, the results results students of the of however, the study in the study can study. we should be applied With be not random conclude applied to the entire only assignment, anything population to the AP about we Statistics should cause in this and not case, students conclude effect. all the in All the students anything we study. can at conclude about With this cause is random school. that students and assignment, With effect. random at All this however, assignment, school can conclude who we can listen we can conclude is to that conclude music AP that Statistics while that there studying there is a is students have a cause-and-effect lower who GPAs listen than relationship to music those while who between do studying not listening have to to lower to music GPAs while than studying. those and We who GPA, don t for not but know all listen only the why for students to their music AP GPAs while Statistics the are studying. school. lower, students however. We who don t why took and part we in the can t study. apply these results to any larger group of students.

6 The Challenges of Establishing Causation A well-designed experiment tells us that changes in the explanatory variable cause changes in the response variable. Lack of realism can limit our ability to apply the conclusions of an experiment to the settings of greatest interest. In some cases it isn t practical or ethical to do an experiment. Consider these questions: Does texting while driving increase the risk of having an accident? Does going to church regularly help people live longer? Does smoking cause lung cancer? It is sometimes possible to build a strong case for causation in the absence of experiments by considering data from observational studies.

The Challenges of Establishing Causation When we can t do an experiment, we can use the following criteria for establishing causation. The association is strong. The association is consistent.

7 The Challenges of Establishing Causation When we can t do an experiment, we can use the following criteria for establishing causation. The association is strong. The association is consistent. Larger values of the explanatory variable are associated with stronger responses. The alleged cause precedes the effect in time. The alleged cause is plausible. Discuss how each of these criteria apply to the observational studies of the relationship between smoking and lung cancer.

8 Data Ethics Complex issues of data ethics arise when we collect data from people. Here are some basic standards of data ethics that must be obeyed by all studies that gather data from human subjects, both observational studies and experiments. Basic Data Ethics All planned studies must be reviewed in advance by an institutional review board charged with protecting the safety and well-being of the subjects. All individuals who are subjects in a study must give their informed consent before data are collected. All individual data must be kept confidential. Only statistical summaries for groups of subjects may be made public.

9 Section 4.3 Summary In this section, we learned that Inference about the population requires that the individuals taking part in a study be randomly selected from the larger population. A well-designed experiment that randomly assigns treatments to experimental units allows inference about cause-and-effect. Lack of realism in an experiment can prevent us from generalizing its results. In the absence of an experiment, good evidence of causation requires a strong association that appears consistently in many studies, a clear explanation for the alleged causal link, and careful examination of possible lurking variables. Studies involving humans must be screened in advance by an institutional review board. All participants must give their informed consent, and any information about the individuals must be kept confidential.

10 Looking Ahead In the next Chapter We ll learn how to apply the mathematics of chance as a basis for inference. We ll learn about Randomness and Probability Simulations Probability Rules Conditional Probability and Independence

4.1. Title: data analysis (systems analysis). 4.2. Annotation of educational discipline: educational discipline includes in itself the mastery of the

4.1. Title: data analysis (systems analysis). 4.4. Term of study: 7th semester. 4.1. Title: data analysis (applied mathematics). 4.4. Term of study: 6th semester. 4.1. Title: data analysis (computer science).