Statistical data type

Data Type	Possible values	Example usage	Level of measurement	Distribution	Scale of relative differences	Permissible statistics	Regression analysis
binary	0, 1 (arbitrary labels)	binary outcome ("yes/no", "true/false", "success/failure", etc.)	nominal scale	Bernoulli	incomparable	mode, Chi-squared	logistic,probit
categorical	1, 2, ..., K (arbitrary labels)	categorical outcome (specific blood type,political party, word, etc.)		categorical			multinomial logit,multinomial probit
ordinal	integer orreal number(arbitrary scale)	relative score, significant only for creating a ranking	ordinal scale	categorical??	relative comparison		ordinal regression(ordered logit,ordered probit)
binomial	0, 1, ..., N	number of successes (e.g. yes votes) out of Npossible	interval scale??	binomial,beta-binomial, etc.	additive??	mean,median,mode,standard deviation,correlation	binomial regression(logistic,probit)
count	nonnegativeintegers (0, 1, ...)	number of items (telephone calls, people, molecules, births, deaths, etc.) in given interval/area/volume	ratio scale	Poisson,negative binomial, etc.	multiplicative	All statistics permitted for interval scales plus the following:geometric mean,harmonic mean,coefficient of variation	Poisson, negative binomial regression
real-valuedadditive	real number	temperature, relative distance,location parameter, etc. (or approximately, anything not varying over a large scale)	interval scale	normal, etc. (usually symmetric about themean)	additive	mean,median,mode,standard deviation,correlation	standardlinear regression
real-valuedmultiplicative	positive real number	price, income, size,scale parameter, etc. (especially when varying over a large scale)	ratio scale	log-normal,gamma,exponential, etc. (usually a skeweddistribution)	multiplicative	All statistics permitted for interval scales plus the following:geometric mean,harmonic mean,coefficient of variation	generalized linear modelwithlogarithmiclink