202notes2__Probability

# 202notes2_Probabili - Incidental Sample sample of certain available group only given option of one population Biased Sample systematic error self

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PROBABILITY P = # ways an event can occur # events possible Ex: flipping a coin and getting a tail 1 way to get a tail 1 p = 2 events (head or tail) = 2 = .5 = 50% Additive Rule: "OR" Rule Ex: getting an Ace of Hearts or an Ace of Diamonds 1 1 2 1 52 +52 = 52 = 26 Multiplicative Rule: "And" Rule Ex: getting an Ace and King 4 4 16 52 * 52 = 2704 =.006 *probability of occurrence under normal curve ODDS: NOT probability Partition of events, not probability Frequency of occurrence vs. Non-occurrence Ex: Horse runs 52 races, wins 20, loses 32 For = 20:32 Against = 32:20 WHY KNOW THIS: Want to know if sample is indicative of what is really going on Bigger sample = Better estimate, more samples is better A sample is just a snapshot and although usually close to actual, there is fluctuation between samples and characteristics vary Random Sampling: THE BIG "R" Each element has equal chance in sample Pull many samples How to get Random Sample - "count off" - computer generated list

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Unformatted text preview: Incidental Sample : sample of certain available group, only given option of one population Biased Sample : systematic error, self selection MEAN of the Means • Better than any one mean, more samples • To see how well sample mean estimates true mean, do confidence interval HYPOTHESI Null Hypothesis = Ho • Do not expect any difference • To be nullified Alternative Hypothesis = reject Ho • Assume correct and disprove then favor alternative ALPHA : .001 .01 .05 .10 • The less strict (.05 less strict than .001) the easier to have a "winner" • Importance/involvement determines appropriate strictness Ex: medical procedure - very strict, little margin for error *every industry has different "norm", mean of mean that is acceptable 2-Tail Test : don't know direction of preference/difference (can't predict difference) 1-Tail Test can predict direction of difference (predict winner)...
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## This note was uploaded on 04/25/2011 for the course MKT 202 taught by Professor Hillman during the Spring '10 term at DePaul.

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202notes2_Probabili - Incidental Sample sample of certain available group only given option of one population Biased Sample systematic error self

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