lecture11_2slides

# lecture11_2slides - Statistics 528 Lecture 11 Big Picture...

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Statistics 528 - Lecture 11 1 Statistics 528 - Lecture 11 Prof. Kate Calder 1 Big Picture Collect Data (experiment or sample survey) Exploratory Data Analysis Formal Statistical Inference Statistics 528 - Lecture 11 Prof. Kate Calder 2 We need to collect trustworthy data and be able to judge the quality of data produced by others in order to be able to do formal statistical inference (generalize results in samples). We do not want to base conclusions or inferences on anecdotal evidence . Sources of available data: Statistical Abstract of the United States Government databases Internet

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Statistics 528 - Lecture 11 2 Statistics 528 - Lecture 11 Prof. Kate Calder 3 Observation vs. Experiment An observational study observes individuals and measures variables of interest but does not attempt to influence the individuals’ responses. An experiment imposes some treatment on individuals in order to observe their responses. Statistics 528 - Lecture 11 Prof. Kate Calder 4 Samples A population is the collection of individuals (do not have to be people) we are interested in studying. A sample is a subset of the population. If we can measure every individual in our population we have census.
Statistics 528 - Lecture 11 3 Statistics 528 - Lecture 11 Prof. Kate Calder 5 Example: Some people believe that exercise raises the body’s metabolic rate for as long as 12 to 24 hours enabling us to continue to burn off fat after our workout has ended. In a study of this effect, subjects were asked to walk briskly on a treadmill for several hours. Their metabolic rates were measured before and 12 hours after the exercise. Question: Was this study an experiment? Why or why not? Question: What are the explanatory and response variables? Statistics 528 - Lecture 11 Prof. Kate Calder 6 Design of Experiments Terminology: The individuals on which the experiment is done are called the experimental units . When the units are human beings, they are called subjects . A specific experimental condition applied to the units is called a treatment . The explanatory variables that you are think may explain the effect of the treatments are called factors . The specific values of each of the factors are called levels . An experimental design describes how the treatments are assigned to the experimental units.

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Statistics 528 - Lecture 11 4 Statistics 528 - Lecture 11 Prof. Kate Calder 7 Example: What are the effects of repeated exposure to an advertising message? The answer depends both on the length of the ad and on how often it is repeated. An experiment is conducted with undergrad students of OSU to investigate this question. All subjects viewed a 60- minute episode of a television show that included ads for a new ice cream. Some subjects saw a 30-second ad; others, a 90-second version. The same ad was repeated 1, 3, or 5 times during the program. After
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lecture11_2slides - Statistics 528 Lecture 11 Big Picture...

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