chapter 20 m303 final

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chapter 20 m303 final
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  1. •A multivariate technique used for
    studying the interdepedent relationship between two or more
    categorical variables (i.e., nominal- or ordinal-level)

    •We usually seek to investigate
    the influence of one variable (Independent variable) on another variable
    (Dependent variable)

    •consider the joint
    distribution of sample elements across variables

    •It is the most used multivariate
    data analysis technique
    •Two-Way Cross Tabulations
  2. •It
    tests the degree to which the two variables in a cross-tabulation analysis are
    independent of one another.

    •Ho:
    variables are independent .

    •Ha:
    variables are  interdependent.
    •Pearson chi-square (χ2) test of independence
  3. •A commonly used technique used to
    determine whether two groups differ on some characteristic assessed on a
    continuous measure

    •Examples

    •Satisfaction ratings, females
    versus males

    •Age in years, customers versus
    non-customers

    •Number of units purchased,
    households with children versus households without children
    • •Independent Samples t-test for
    • Means
  4. •A technique for comparing two
    means when scores for both variables are provided by the same sample

    •Examples

    •Attitude toward the brand
    measures before
    and after reviewing
    a 30-second ad

    •Price perceptions for a local
    store versus a competitor (i.e., applying the same measure to different
    objects)
    •Paired Sample t-test for Means
  5. •A statistical technique used with
    a continuous dependent (outcome) variable and one or more categorical
    independent variables

    Advantages of Using Over a Series of t-tests to Examine Differences Across Groups

    •Applicable to more than two
    group.

    •Applicable to more than one
    categorical independent variable
    •Analysis of Variance (ANOVA)
  6. •A statistical technique used with
    a continuous dependent (outcome) variable and one independent variable
    •One-way ANOVA
  7. A statistical technique used with
    a continuous dependent (outcome) variable and two or more independent
    variables; interaction
    •Two-way ANOVA
  8. •A statistic that indicates the
    degree of linear association between two continuous variables

    •The correlation coefficient can
    range from -1 (inverse relationship) to +1 (direct relationship)

    •Note:  Correlation ≠
    Causation; Correlation = Relationship

    •Examples

    •Relationship
    between advertising expenditure and sales

    •Relationship
    between the number of hours studied and exam grade
    • •Pearson Product-Moment
    • Correlation Coefficient
  9. a statistical procedure foranalyzing the relationship between 1 IV and 1 DV. (also called Bivariate regression)

    A statistical technique used to
    derive an equation that relates a single continuous dependent variable to a single independent variable
    Simple Regression
  10. a statistical procedure for
    analyzing the relationship   >=2 IVs, 1
    DV.

    A statistical technique used to
    derive an equation that relates a single continuous dependent variable to two
    or more independent
    variables
    Multiple regression
  11. •R2 is the measure of the strength of
    the linear relationship between X (IV) and Y (DV).

    •R2  measures
    the percent of the total variation in Y that is “explained” by the variation in
    X.
    Simple Regression - Coefficient of determination (R2)

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