Hyp Testing, Crosstabs, and Chi-square

# Hyp Testing, Crosstabs, and Chi-square - Hypothesis Testing...

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Hypothesis Testing Hypothesis Testing Formulate H 0 and H 1 Choose Significance Level Select Appropriate Test Data Collection Determine Critical Value Compare the Probability Reject or FTR

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Hypothesis Testing Steps: Hypothesis Testing Steps: The Basics The Basics Null hypothesis (H 0 ) - statement of no difference or no effect it's the status quo Step 1: Formulate H 0 & H 1 ex. Using age to predict bottled water intake Alternative (H 1 ) - some difference or effect is expected opposite of the status quo
Null hypothesis (H 0 ) - age has no effect on bottled water intake. H 0 & H & H 1 Alternative (H 1 ) - younger consumers (< 30 years) drink significantly more bottled water than older consumers ( 30 years). Next question: if there is a difference, is it: statistically significant ???

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Significance Basics Significance Basics o Significance Level: specifies the probability at which you are willing to risk an incorrect conclusion . α = .05 means that it's acceptable to commit a Type I error 5 times out of 100 i.e., the probability of making a Type I error:
Types of Errors: a. Type I ( α )- probability of rejecting a true null "finding an effect when there isn't one" "a false positive" saying age makes a difference in bottled water intake when it really doesn't Significance Basics Significance Basics

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Power (1- β ) - rejecting a false null "finding an effect when it exists" b. Type II ( β ) - probability of FTR a false null "missing an effect when it exists" "false negative" saying age doesn't make a difference in bottled water intake when it really does n = (1 - β ) Significance Basics Significance Basics
Frequencies Frequencies - using percentages to test a relationship - 79% of those < 30 drink bottled water Cross-Tabs Cross-Tabs Cross Cross - - Tabulation Tabulation - - cross classifies categories of one variable with the categories of one or more others. describes two or more variables Ordinal Data or Less: Ordinal Data or Less:

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Cross-Tabs Cross-Tabs row by column analysis of the frequency counts Independent Variables: Column (Banner) Dependent Variable(s): Row (stubs) Sampling: need 5 expected observations per cell Age: < 30 30 total Drink: yes 79 43 122 no 21 57 78 total 100 100 200
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## This note was uploaded on 06/23/2011 for the course MKTG 352 taught by Professor ? during the Summer '10 term at South Carolina.

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Hyp Testing, Crosstabs, and Chi-square - Hypothesis Testing...

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