Data sequences and subjective sampling distributions

Subjective Sampling Distributions and Conservatism 1

When people revise subjective probabilities in light of data, revisions a r e less than the amount prescribed by the normative model, Bayes's theorem. Previous research suggests that this results from the subjects' lack of understanding of the implications of the data; i.e., from inaccurate subjective sampling distributions. This experiment examined the effects on conservatire revisions of trai...

Sampling Distributions Sampling Distributions

Sampling and Sampling Distributions

A sample is a group of objects or readings taken from a population for counting or measurement. We shall distinguish between two kinds of populations — finite populations and infinite populations. The sample must be random, meaning that all possible samples of a particular size must have equal probabilities of being chosen from the population. This will prevent bias in the sampling process. Mos...

Near-optimal Distributions for Data Matrix Sampling

We give near-optimal distributions for the sparsification of large m n matrices, where m ! n, for example representing n observations over m attributes. Our algorithms can be applied when the non-zero entries are only available as a stream, i.e., in arbitrary order, and result in matrices which are not only sparse, but whose values are also highly compressible. In particular, algebraic operatio...

Probability and Sampling Distributions

When an experiment is conducted, such as tossing coins, rolling a die, sampling for estimating the proportion of defective units, several outcomes or events occur with certain probabilities. These events or outcomes may be regarded as a variable which takes different values and each value is associated with a probability. The values of this variable depends on chance or probability. Such a vari...