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For example, parameter data consists of the different values for varying conditions in an experiment (e.g., temperature, time). The measured data (or variables) are the measurements taken in the experiment under these varying conditions. Many statistical databases are sparse with many null or zero values.
How high, or how low, is determined by the value of the attribute (and in fact, an attribute could be just the word "low" or "high"). [1] For example see: Binary option ) While an attribute is often intuitive, the variable is the operationalized way in which the attribute is represented for further data processing .
Many examples and problems come from business and economics. Importance: Greatly extended the scope of applied Bayesian statistics by using conjugate priors for exponential families. Extensive treatment of sequential decision making, for example mining decisions. For many years, it was required for all doctoral students at Harvard Business School.
Typically a population is very large, making a census or a complete enumeration of all the values in that population infeasible. A sample thus forms a manageable subset of a population. In positivist research, statistics derived from a sample are analysed in order to draw inferences regarding the population as a whole
In the field of statistics, these alternative interpretations allow for the analysis of different datasets using distinct methods based on various models, aiming to achieve slightly different objectives. When comparing the competing schools of thought in statistics, pragmatic criteria beyond philosophical considerations are taken into account.
All classical statistical procedures are constructed using statistics which depend only on observable random vectors, whereas generalized estimators, tests, and confidence intervals used in exact statistics take advantage of the observable random vectors and the observed values both, as in the Bayesian approach but without having to treat constant parameters as random variables.
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For example, count data requires a different distribution (e.g. a Poisson distribution or binomial distribution) than non-negative real-valued data require, but both fall under the same level of measurement (a ratio scale). Various attempts have been made to produce a taxonomy of levels of measurement.