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Exam 2 Part III - Flashcards

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Class:MKTG 4154 - Marketing Research
Subject:Marketing
University:Virginia Polytechnic Institute And State University
Term:Spring 2013
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Test of differences an investigation of a hypothesis that 2 or more groups differ with respect to measures of a variable (behavior, characteristics, beliefs)
Choosing the right statistic depends on:
  1. Type of measurement
  2. Nature of the comparison
  3. Number of groups to be compared
x-squared test testing statistical significance of contingency table
  • compare the observed frequencies with expected frequencies 
Testing Hypotheses
  1. examine statistical significance of observed contingency table
  2. examine whether the difference between observed and expected values are consistent with hypothesized prediction
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Paired samples t-test compares the scores of 2 interval variables drawn from related populations
z-test comparing 2 proportions
  • Test hypothesis that proportions are significantly different 2 independent samples
  • requires sample size>30
Analysis of Variance (ANOVA) investigating the effects of one treatment variable on an interval scaled dependent variable
Between group variances sum of the differences between the group mean and the grand mean summed over all groups for a given set of observations
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Within-group error sum of the differences between the observed values and the group mean 
also called total error variance
F-test used to determine whether there is more variability in the scores of one sample than in the scores of another
General linear model a way of explaining and predicting a dependent variable based on fluctuations (variation) from its mean due to changes in independent variables
Multiple regression analysis An analysis of association where the effects of 2 or more independent variables on a single, interval scaled dependent variable investigated simultaneously
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Parameter estimate choices
  • Raw regression estimates (b1): used if the purpose of the regression analysis is forecasting
  • standardized regression estimates (B1): advantage of a constant scale, used when researcher is trying to explain some outcomei
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 Test of differencesan investigation of a hypothesis that 2 or more groups differ with respect to measures of a variable (behavior, characteristics, beliefs)
 Choosing the right statistic depends on:
  1. Type of measurement
  2. Nature of the comparison
  3. Number of groups to be compared
 x-squared testtesting statistical significance of contingency table
  • compare the observed frequencies with expected frequencies 
 Testing Hypotheses
  1. examine statistical significance of observed contingency table
  2. examine whether the difference between observed and expected values are consistent with hypothesized prediction
 Paired samples t-testcompares the scores of 2 interval variables drawn from related populations
 z-testcomparing 2 proportions
  • Test hypothesis that proportions are significantly different 2 independent samples
  • requires sample size>30
 Analysis of Variance (ANOVA)investigating the effects of one treatment variable on an interval scaled dependent variable
 Between group variancessum of the differences between the group mean and the grand mean summed over all groups for a given set of observations
 Within-group errorsum of the differences between the observed values and the group mean 
also called total error variance
 F-testused to determine whether there is more variability in the scores of one sample than in the scores of another
 General linear modela way of explaining and predicting a dependent variable based on fluctuations (variation) from its mean due to changes in independent variables
 Multiple regression analysisAn analysis of association where the effects of 2 or more independent variables on a single, interval scaled dependent variable investigated simultaneously
 Parameter estimate choices
  • Raw regression estimates (b1): used if the purpose of the regression analysis is forecasting
  • standardized regression estimates (B1): advantage of a constant scale, used when researcher is trying to explain some outcomei
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