candyloveee
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how do you distinguish between these different tests quickly?
chi-square , Analysis of Variance (F), regression (r2), correlation (r), principal
components analysis (l).

say if you had some statments and had to say which test was appropriate:

e.g.

Predicting additive and interactive effects of diet and cage size
on blood cortisol concentrations in battery chickens.

Comparing sex ratios of three populations of jacanas, one
monogamous, one polygynous, and one polyandrous.

Testing for an effect of maternal diet during gestation on
subsequent dispersal distance of offspring in lizards.
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ztibor
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(Original post by candyloveee)
how do you distinguish between these different tests quickly?
chi-square , Analysis of Variance (F), regression (r2), correlation (r), principal
components analysis (l).
The test to be used depends on the number of samples or the variables,
on the type of data or scale of neasurement and on that what is the question
THe type of data or the scale of measurement may be
- interval scale
- ordinal scale
- nominal scale
For the question: wether the difference is significant
- for one sample:
t-test with one sample (data measured on interval scale)
Wilcoxon-test (ordinal scale)
khi-square test (nominal scale)
- for 2 samples
t-test of 2 samples or F-test or analysis of variance (data measured on interval scale)
Mann-Whitney test (data measured on ordinal scale)
khi-square test (data measured on nominal scale)
- for more than 2 samples
Analysis of Variance (data measured on interval scale)
Kruskall-Wallis test (ordinal scale)
khi-square test (nominal scale)

For the question: is there strong correlation between variables
- for 2 variables
correlation (interval scale)
Rank correlation (ordinal scale )
khi-square test (nominal scale)
- for 2 or more variables
Regression analysis (interval scale)
for more than 2 variables (all measured on interval sacle)
-partial correlation
- Analysis of factors
- Analysis of cluster
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