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Unlocking the Mysteries of Hypothesis Testing

What's this all about?. HypothesisAn educated guessA claim or statement about a property of a populationThe goal in Hypothesis Testing is to analyze a sample in an attempt to distinguish between population characteristics that are likely to occur and population characteristics that are unlikely t

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Unlocking the Mysteries of Hypothesis Testing

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    1. Brent Griffin Revised Fall 2006 Unlocking the Mysteries of Hypothesis Testing

    2. What’s this all about? Hypothesis An educated guess A claim or statement about a property of a population The goal in Hypothesis Testing is to analyze a sample in an attempt to distinguish between population characteristics that are likely to occur and population characteristics that are unlikely to occur.

    3. Null Hypothesis vs. Alternative Hypothesis Type I vs. Type II Error ? vs. ? The Basics

    4. Null Hypothesis vs. Alternative Hypothesis Null Hypothesis Statement about the value of a population parameter Represented by H0 Always stated as an Equality Alternative Hypothesis Statement about the value of a population parameter that must be true if the null hypothesis is false Represented by H1 Stated in on of three forms > < ?

    5. Type I vs. Type II Error

    6. Alpha vs. Beta a is the probability of Type I error b is the probability of Type II error The experimenters (you and I) have the freedom to set the ?-level for a particular hypothesis test. That level is called the level of significance for the test. Changing a can (and often does) affect the results of the test—whether you reject or fail to reject H0.

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