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All four sets have identical statistical parameters, but the graphs show them to be considerably different. Anscombe's quartet comprises four datasets that have nearly identical simple descriptive statistics, yet have very different distributions and appear very different when graphed. Each dataset consists of eleven (x, y) points.
Variants include pooled cross-sectional data, which deals with the observations on the same subjects in different times. In a rolling cross-section , both the presence of an individual in the sample and the time at which the individual is included in the sample are determined randomly.
One makes a set of specific observations, and seeks to make a general principle based on those observations, which will point to certain other observations that would naturally result from either a repeat of the experiment or making more observations from a slightly different set of circumstances.
Structure is a fundamental and sometimes intangible notion covering the recognition, observation, nature, and stability of patterns and relationships of entities. From a child's verbal description of a snowflake, to the detailed scientific analysis of the properties of magnetic fields , the concept of structure is an essential foundation of ...
In descriptive statistics, summary statistics are used to summarize a set of observations, in order to communicate the largest amount of information as simply as possible. Statisticians commonly try to describe the observations in a measure of location, or central tendency, such as the arithmetic mean
Pattern recognition is the task of assigning a class to an observation based on patterns extracted from data. While similar, pattern recognition (PR) is not to be confused with pattern machines (PM) which may possess (PR) capabilities but their primary function is to distinguish and create emergent patterns.
Suppose members p i of a population P are observed with respect to their success in a written verbal intelligence test. Such observations may be described as a mapping from the observed population to the set of possible scores, say, R = {1,...,10}: P q1 → R, where q1 is the sense in which a specific score is assigned to every individual in the observed population P, i.e., q1 is "verbal ...
Situation sampling involves the study of behavior in many different locations, and under different circumstances and conditions. [2] By sampling different situations, researchers reduce the chance that the results they obtain will be particular to a certain set of circumstances or conditions.