Here is a decision chart to pick your test
Table of contents:
Type | Samples | Sample type | Test | Askia | |
A |
Mean | 2 | Independent | T-test | Significance (Numeric) |
B | Mean | 2 | Paired | Paired T-Test | Col significativity on Numeric |
C | Mean | 2 | Paired | Wilcoxon rank test | Col significativity on Numeric |
D | Mean | 3 | Independent | Anova With One Way | Col significativity on Numeric |
E | Mean | 2 | Paired | Anova With Random subject | Col significativity on Numeric |
F | Proportion | 2 | Independent | Z-test for proportions | Col significativity on closed |
G | Proportion | 2 | Independent | Khi² | Significance (Closed) |
I | Proportion | 3 | Independent | Khi² + Marscuilo post-hoc | Significance (Closed) |
J | Proportion | 3 | Independent | Khi² + Cochran adjustment | Col on Col Sig (Closed) |
A- Significance (Numeric) (T-test)
A |
Mean | 2 | Independent | T-test | Significance (Numeric) |
B- Col significativity on Numeric (Paired T-test)
B | Mean | 2 | Paired | Paired T-Test | Col significativity on Numeric |
C- Col significativity on Numeric (Wilcoxon rank test)
C | Mean | 2 | Paired | Wilcoxon rank test | Col significativity on Numeric |
D-Col significativity on Numeric (Anova One Way + Tuckey HSD test)
D | Mean | 3 | Independent | Anova With One Way | Col significativity on Numeric |
E-Col significativity on Numeric (Anova with Random Subject)
E | Mean | 2 | Paired | Anova With Random subject | Col significativity on Numeric |
E-Col significativity on closed (Z_test for proportions)
F | Proportion | 2 | Independent | Z-test for proportions | Col significativity on closed |
G-Signficance (Closed) (Khi²)
G | Proportion | 2 and + | Independent | Khi² | Significance (Closed) |
I-Signficance (Closed) (Khi² + Marscuilo post-hoc)
I | Proportion | 3 | Independent | Khi² + Marscuilo post-hoc | Significance (Closed) |
J-Col on Col Sig (Closed) (Khi²+ Cochran adjustment)
J | Proportion | 3 | Independent | Khi² + Cochran adjustment | Col on Col Sig (Closed) |
With the Cochran–Mantel–Haenszel (CMH) test adjustment
Which allows the comparison of two groups on a dichotomous/categorical response. It is used when the effect of the explanatory variable on the response variable is influenced by covariates that can be controlled. It is often used in observational studies where random assignment of subjects to different treatments cannot be controlled, but influencing covariates can.
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