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Stat 281: Introduction to Probability and Statistics A prisoner had just been sentenced for a heinous crime and was returned to his cell. An inquisitive guard could not wait to ask him about the outcome. Guard: “What did you get for a sentence?” Prisoner: “I could choose life or 100 years.” Guard: “And what did you choose?” Prisoner: “Well, life, obviously. Statistically speaking, that is the shorter sentence.”
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I need email from: Missing or invalid email addresses: –Beardt, Bradley S. –Coulter, David P. –Jacobson, Michael H. –Keating, Maxon J. –Magnuson, Melissa L. Anyone else who did not receive an email from me (about the room change)
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email and web page My email and web page are on the syllabus If you have campus email, just type “Dwight Galster” and it should come up Otherwise it is dwight.galster@sdstate.edu dwight.galster@sdstate.edu My web page is http://learn.sdstate.edu/dwight.galster http://learn.sdstate.edu/dwight.galster Once at the web page click on the course in the schedule to get to the course page. PowerPoints and assignments will be posted on the web page I suggest you bookmark the course page and visit it often.
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Keys to Success Definitions are crucial in stats class. If you don’t know the precise meaning of a word, the whole point of the sentence/paragraph/chapter could be lost! Concepts are important in stats class. –Lots of formulas—don’t plug in numbers blindly—understand why –Review and integrate
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Definitions Data (is/are?) Population (of? Not a number) Finite/Infinite/Practically Infinite Sample (proper subset, finite) Variable (response, random) Parameter/Statistic Greek/Latin Experiment/Observational Study
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Probability vs. Statistics Probability: Properties of population are known. Make predictions about sample. Statistics: Sample is known. Guess (estimate) properties of population. Statistics (is/are?) –Descriptive –Inferential
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Types of Data (Variables) Categorical (Class, Attribute, Qualitative) Numeric (Quantitative) –Discrete (Finite or Infinite) –Continuous (always Infinite) Measurement Scales –Nominal –Ordinal –Interval –Ratio
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Identify the Data Types 1.The daily high temperature (°F) in Brookings. 2.The make of automobile driven by each student. 3.The defect status of 9 volt batteries being tested. 4.The weight of a lead pencil. 5.The length of time billed for a long distance call. 6.Which brand of cereal children eat for breakfast. 7.The genre of a book checked out of the library. 8.The time until a pain reliever begins to work.
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Variation No matter what the response variable: there will always be variability in the data. One of the primary objectives of statistics: measuring and characterizing variability. Controlling (or reducing) variability in a manufacturing process: statistical process control.
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Are you above average? The vast majority of people have more than the average number of legs. “When she told me I was average, she was just being mean.” You know how dumb the average person is? Well, half the population is dumber than that!
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Sampling Methods Sampling Frame Representative Biased and Unbiased Sampling Methods –Convenience –Volunteer –Judgment –Probability
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Probability Sample Designs Simple Random Sample Systematic Sample Stratified –Proportional (Quota) Cluster
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