Dependent Variable
                                                 Metric      Non-Metric
                                                           • Discriminant 
                 Independent       Metric      Regression      Analysis
                  Variable(s)                              •Binary/Logistic 
                                                              regression
                                Non-Metric     Hypothesis   Chi-square Test
                                                 testing
  • If the independent variable (which is non-
   metric) has two categories, we will use t-test
  • And if the independent variable has more than 
   two categories we will use F-test (ANOVA)
                    ANOVA
   • ANOVA uses F statistics which is the ratio of variances 
     between groups and variances with-in groups (error 
     variance)
   • If group means do not differ significantly, one can 
     believe that all group means come from same 
     population and do not differ
   • Larger the F statistics  Larger is the difference between 
     groups as compared to with-in group differences
   • F Statistics < 1  Indicates no significant difference in 
     the group means and thus H  is correct.
                         o
             Assumptions
   Normality:
   • Ho  Data are normally distributed
   • Steps to check overall normality
    –Analyze  Non parametric tests  Legacy dialogs  One sample K S test
    – p-value of K S Test > 0.05  Data are normally distributed
    –p-value of K S Test < 0.05  Use Non-parametric test
   • Steps to check category-wise normality
    –Analyze  Descriptive  Explore  Plots  Tick Normality plots with stats
   • If your sample size for different categories is comparable, and any 
    one or two categories are not normally distributed, even then, F & 
    t are very robust tests
    - Andy Field
                     Assumptions
    Homogeneity of Variance:
    • We assume that each sample comes from a population 
      with same variance. And thus, variance across samples is 
      homogeneous.
    • H   Variances across groups is equal or Homogeneous
        o
    • Steps to check overall Variance
       –Analyze  Descriptive statistics  Descriptives  Options  Tick 
        Variance 
    • Steps to check category-wise Variance
       –Analyze  Compare Means  Means  Options  Tick Variance