statistics-for-design - Statistics for Design Brian Bailey...

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Statistics for Design Brian Bailey
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Announcements HW 3 due Friday Evaluation results due Friday Get posters done over break, start printing posters on the 28 th
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Canonical Result Graph 0 5 10 15 20 25 Interface AI n t e r f a c e B Task Time (secs)
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Canonical Result Graph 0 5 10 15 20 25 Interface AI n t e r f a c e B Task Time (secs) Users performed faster with Interface B ( μ =12.3) than with Interface A ( μ =18.4; p <.05)
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Today’s Goals Understand hypothesis testing formulation, types of errors, and power Understand p-value what is says and what it does not say Assess the credibility of a test
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Bigger Picture Knowing good design increasingly requires knowledge of statistics Statistics allows inferences to be made about populations by studying samples Know which tests to perform, how to perform them, how to interpret results
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Sampling A population is the entire collection of the outcomes of interest A sample is a subset of the population A simple random sample (N) each sample of size N is equally likely
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Summary Statistics Arithmetic mean Variance Standard deviation n i i X n X 1 1 n i i X X n 1 2 2 ) ( 1 1 n i i X X n 1 2 ) ( 1 1
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Random Variable Function that assigns values to all possible outcomes of an experiment e.g., completion time of a task Two types discrete: maps values from ordered set continuous: maps values from interval Mapping from probability distribution
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Probability Distributions 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 123456789 P(X)
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This note was uploaded on 03/04/2012 for the course CS 465 taught by Professor Karahalios,k during the Fall '08 term at University of Illinois, Urbana Champaign.

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statistics-for-design - Statistics for Design Brian Bailey...

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