David B. Howell
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A. Objectives—students will be able to
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1. define sample;
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2. describe and give examples of random sample;
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3. Iist factors compromising randomness;
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4. describe variations among samples.
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B. The experimental question—What percent of the population prefers pepsi to Coca-Cola?
C. Issues, and some possible resolutions—
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What population? (This class. The school. Hew Haven. Kids. people over 40. Basketball players.)
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How do we find out? (Ask. Give a questionnaire. Do a taste test!)
Let’s start with this class again. And let’s do a taste test. [paper cups, chilled cans of pepsi and Coca-Cola, coding on cups, pouring out of sight of tasters, etc. -here are many fair testing issues. Does it matter which is tasted first? Which is on the right? Chilled or warm? Influence of other tasters? Are the results significantly different than chance? All relate to objectives about sampling procedures and/or tests of significance. None is central to this Unit. Prepare for a long detour if the issues become important to your class. To stay on track, establish a procedure with a minimum of debate, emphasize the need for procedural consistency, and get on with it.]
Use Worksheet 1 to record data. Answer 1 is “Prefer pepsi.” [Note there are at least
two
classes of answers not recorded: “prefer Coca-Cola” and “Ho preference.”]
[Form samples in different ways within the one class. The simplest techniques to add together different combinations of small samples to get larger ones. Students who are experienced in listing combinations might list all possible combinations of 3 small samples and record their data. Remember, however, that this Lesson does HOT center on combinatorics! Compare samples as in Lesson 1.]
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D. Observations and discussion to Objectives—
Did we collect data from the entire population? What is the difference between a sample and the entire population? Which of the samples were random? Which were not? What is the difference in the way they were chosen? Describe the differences in results across samples. Can any differences be attributed to whether or not the samples were chosen randomly? What about the range of results among samples? Does sample size matter?