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Choosing the right statistic
The Virtual Statistical Assistant
What statistical analysis should I use? Statistical
analyses using SPSS
http://www.ats.ucla.edu/stat/spss/whatstat/whatstat.htm
From http://www.ats.ucla.edu/stat/mult_pkg/whatstat/default.htm
What statistical analysis should I use?
The following table shows general guidelines for choosing a statistical
analysis. We emphasize that these are general guidelines and should not be
construed as hard and fast rules. Usually your data could be analyzed in
multiple ways, each of which could yield legitimate answers. The table below
covers a number of common analyses and helps you choose among them based on the
number of dependent variables (sometimes referred to as outcome variables), the
nature of your independent variables (sometimes referred to as predictors). You
also want to consider the nature of your dependent variable, namely whether it
is an interval variable, ordinal or categorical variable, and whether it is
normally distributed (see
What is the difference between categorical, ordinal and interval variables?
for more information on this). The table then shows one or more statistical
tests commonly used given these types of variables (but not necessarily the only
type of test that could be used) and links showing how to do such tests using
SAS, Stata and SPSS.
|
Number of
Dependent
Variables |
Nature of
Independent
Variables |
Nature of Dependent
Variable(s) |
Test(s) |
How to
SPSS |
|
1 |
0 IVs
(1 population) |
interval & normal
|
one-sample t-test |
SPSS |
|
ordinal or interval |
one-sample median |
SPSS |
|
categorical
(2 categories) |
binomial test |
SPSS |
| categorical |
Chi-square goodness-of-fit |
SPSS |
|
1 IV with 2 levels
(independent groups)
|
interval & normal |
2 independent sample t-test |
SPSS |
|
ordinal or interval |
|
Wilcoxon-Mann Whitney test |
SPSS
|
|
categorical |
Chi- square test |
SPSS
|
|
Fisher's exact test |
SPSS
|
|
1 IV with 2 or more levels (independent groups) |
interval & normal
|
one-way ANOVA |
SPSS |
|
ordinal or interval |
Kruskal Wallis |
SPSS
|
|
categorical |
Chi- square test |
SPSS
|
|
1 IV with 2 levels
(dependent/matched groups) |
interval & normal |
paired t-test |
SPSS
|
|
ordinal or interval |
Wilcoxon signed ranks test |
SPSS |
|
categorical |
McNemar |
SPSS |
|
1 IV with 2 or more levels
(dependent/matched groups) |
interval & normal
|
one-way repeated measures ANOVA |
SPSS |
|
ordinal or interval |
Friedman test |
SPSS
|
|
categorical |
repeated measures logistic regression |
SPSS |
|
2 or more IVs
(independent groups) |
interval & normal |
factorial ANOVA |
SPSS |
|
ordinal or interval |
??? |
??? |
|
categorical |
factorial
logistic regression |
SPSS |
|
1 interval IV |
interval & normal |
correlation |
SPSS
|
|
simple linear regression |
SPSS |
|
ordinal or interval |
non-parametric correlation |
SPSS |
|
categorical |
simple logistic regression |
SPSS |
1 or more interval IVs and/or
1 or more categorical IVs |
interval & normal |
multiple regression |
SPSS |
|
analysis of covariance |
SPSS |
|
categorical |
multiple logistic regression |
SPSS |
|
discriminant analysis |
SPSS |
|
2 or more |
1 IV with 2 or more levels
(independent groups) |
interval & normal |
one-way MANOVA |
SPSS |
|
2 or more |
2 or more |
interval & normal |
multivariate multiple linear regression |
SPSS
|
|
2 sets of
2 or more |
0 |
interval & normal |
canonical correlation |
SPSS |
|
2 or more |
0 |
interval & normal |
factor analysis |
SPSS |
|
Number of
Dependent
Variables |
Nature of
Independent
Variables |
Nature of Dependent
Variable(s) |
Test(s) |
How to
SPSS |
This page was adapted from
Choosing the Correct
Statistic developed by James D. Leeper, Ph.D. We thank Professor Leeper for
permission to adapt and distribute this page from our site.
From http://bama.ua.edu/~jleeper/627/choosestat.html
Choosing the Correct Statistical Test
| Number
of
Dependent*
Variables
|
Number
of
Independent**
Variables
|
Type
of
Dependent
Variable(s)
|
Type
of
Independent
Variable(s)
|
Measure |
Test(s)
|
|
1
|
0
(1 population)
|
continuous normal
|
not applicable
(none)
|
mean
|
one-sample t-test
|
|
continuous non-normal
|
median
|
one-sample median
|
|
categorical
|
proportions
|
Chi Square goodness-of-fit, binomial test
|
|
1
(2 independent populations)
|
normal
|
2 categories
|
mean
|
2 independent sample t-test
|
|
non-normal
|
medians
|
Mann Whitney,
Wilcoxon rank sum test
|
|
categorical
|
proportions
|
Chi square test
Fisher's Exact test
|
|
0
(1 population measured twice)
or
1
(2 matched populations)
|
normal
|
not applicable/
categorical
|
means
|
paired t-test
|
|
non-normal
|
medians
|
Wilcoxon signed ranks test
|
|
categorical
|
proportions
|
McNemar, Chi-square test
|
|
1
(3 or more populations)
|
normal
|
categorical
|
means
|
one-way ANOVA
|
|
non-normal
|
medians
|
Kruskal Wallis
|
|
categorical
|
proportions
|
Chi square test
|
|
2 or more
(e.g., 2-way ANOVA)
|
normal
|
categorical
|
means
|
Factorial ANOVA
|
|
non-normal
|
medians
|
Friedman test
|
|
categorical
|
proportions
|
log-linear, logistic regression
|
|
0
(1 population measured
3 or more times)
|
normal
|
not applicable
|
means
|
Repeated measures ANOVA
|
|
1
|
normal
|
continuous |
correlation
simple linear regression
|
|
non-normal
|
non-parametric correlation
|
|
categorical
|
categorical or continuous
|
logistic regression
|
|
continuous
|
discriminant analysis
|
|
2 or more
|
normal
|
continuous
|
multiple linear regression
|
|
non-normal
|
|
|
categorical
|
logistic regression
|
|
normal
|
mixed categorical and continuous
|
Analysis of Covariance
General Linear Models (regression)
|
|
non-normal
|
|
|
categorical
|
logistic regression
|
|
2
|
2 or more
|
normal
|
categorical
|
MANOVA
|
|
2 or more
|
2 or more
|
normal
|
continuous
|
multivariate multiple linear regression
|
|
2 sets of
2 or more
|
0
|
normal
|
not applicable
|
canonical correlation
|
|
2 or more
|
0
|
normal
|
not applicable
|
factor analysis
|
|
