What Analysis Should You Use?
@1,You want to get descriptive statistics of SINGLE variable(s)
@2,You want to get DESCRIPTIVE statistics of two RELATED variables
@3,You want to COMPARE two variables, Independent or Paired
@4,You want to COMPARE more than two variables, Independent or Related
@5,You want to examine ASSOCIATION between two variables
@6,You want to examine ASSOCIATION between more than two variables
@7,Definitions of Terms Used

##1
DESCRIPTIVE STATISTICS & GRAPHS      PROCEDURES TO USE
═══════════════════════════════      ════════════════════
               ┌─ Data is ─────>     Mean, S.D., Box Plot, 5 number summary
               │  Normal             Histogram, Conf. Interval
               │                     (Stat Module)
               │
               │─ Data not ────>     Median, Box Plot
               │  Normal             Histogram, 5 number summary
One Sample  ───│                     (Stat Module)
               │─ Data is
               │  Categorical──>     Frequencies, Pictogram
               │                     (Crosstabs Module)
               │
               └─ Observations─>     Time Series Plot
                  Over Time          (Stat Module)

##2
DESCRIPTIVE STATISTICS & GRAPHS      PROCEDURES TO USE
═══════════════════════════════      ════════════════════
               ┌─ Data are─────>     Pearson's Corr. Coeff. &
               │  Normal             X─Y Scatterplot
               │                     (Stat Module &
               │                     Regression Module)
               │
Two Samples────│─ Data not─────>     Spearmans Corr. Coeff. &
(Related)      │  Normal             X─Y Scatterplot
               │                     (Stat Module &
               │                     Regression Module)
               │
               └─ Data are─────>     Crosstabulations and
                  Qualitative        3─D Bar Chart
                                     (Crosstabs Module)

##3
COMPARISON TESTS ─ TWO SAMPLES                    TEST TO USE
════════════════════════════════                  ═════════════════════
                            ┌─ Data are─────>     Paired t─test
                            │  Normal             (t─test & ANOVA Module)
                            │                      
              │───Samples───│─ Data not ────>     Freidmans Test
              │   Related   │  Normal             (Non-Parametrics Module)
              │             │                      
              │             └─ Data are
              │                Dichotomous──>     McNemar's test
Two Samples ──│                                   (Crosstabs Module)
              │                                    
              │             ┌─ Data are─────>     Ind. Group t─test
              │             │  Normal             (t─test, ANOVA Module)
              │             │                      
              │             │
              │──Samples────│─ Data not─────>     Mann─Whitney U test
                 Independent│  Normal             (Non-Parametrics Module)
                            │                      
                            │
                            └─ Data are─────>     Chi─Square (Homogeniety)
                               Qualitative        (Crosstabs Module)
                                                   
##4
COMPARING MORE THAN TWO SAMPLES               TEST TO USE
═════════════════════════════════════════     ═════════════════════
                          ┌─ Data are─────>   Repeated Measures ANOVA
                          │  Normal           (t─test & ANOVA Module)
                          │
              ┌─Samples───│─ Data not ────>   Friedman ANOVA
              │ Related   │  Normal           (Non-Parametrics Module)
              │           │                    
              │           └─ Data are
              │              Dichotomous──>   Cochran's Q test
              │                               (Non-Parametrics Module)
More than     │                                
Two Samples ──│           ┌─ Data are─────>   Independent Group ANOVA
              │           │  Normal           (t─test & ANOVA Module)
              │           │                    
              │           │
              └─Samples───│─ Data not─────>   Kruskal─Wallis
               Independent│  Normal           (Non-Parametrics Module)
                          │                    
                          │
                          └─ Data are─────>   Chi─Square Test
                             Qualitative       (Crosstabs Module)
                                                
##5

TESTING ASSOCIATION BETWEEN TWO VARIABLES           PROCEDURE TO USE
═════════════════════════════════════════           ═════════════════

                              ┌─ Data are─────>     Pearson Correlation
                              │  Normal             Simple Linear Regression
                              │                     (Regression Module)
                              │                      
                              │
       Two Samples Related────│─ Data not ────>     Spearman Correlation
                              │  Normal             (Regression Module)
                              │                      
                              │─ Data are
                              │  Qualitative──>     Chi-Square (Independence)
                              │                      (Crosstabs Module)
                              │                       
                              └─ Data mixed────>    Spearman Correlation
                                 Normal, Not        (Regression Module)
                                 Normal              
##6


MORE THAN TWO ASSOCIATED VARIABLES           PROCEDURE TO USE
═════════════════════════════════════        ═════════════════

                       ┌─ Data are─────>     Multiple Regression
                       │  Normal             (Regression Module)
                       │                      
                       │
More than 2 Samples  ──│─ Data not─────>     Kendall partial rank─
Related                │  Normal             correlation
                       │                     (N.A.)
                       │
                       └─ Data are─────>     Discriminant Analysis
                          Qualitative        (N.A.)



##7
                                  DEFINITIONS

NORMAL refers to data that are well approximated by a normal (Gaussian)
distribution.

NOT NORMAL refers to quantative data that are not normally distributed.

CATEGORICAL refers to nominal data, such as male/female or brown/blue/black.

QUANTITATIVE refers to data that are numeric such as height, batting average,
number of people per household, etc.

QUALITATIVE refers to data that describe attributes such as hair color,
socioeconomic class, sex, etc.

ASSOCIATED refers to variables where knowledge of one helps predict the
other.

INDEPENDENT refers to variables where knowledge of one does not help predict
others. Usually, samples from unrelated populations.
(continued)
##8
                                  DEFINITIONS
                                  (Continued)

RELATED refers to samples where multiple measures are taken on the same or
related entities. For example, before after weights for a diet, or heights of
twins.

DICHOTOMOUS refers to data that are categorical and can take on only one of
two possible states. For example, yes,/no or on/off. VARIABLE refers to the
observed measure, such as height, hair color, etc.
