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Dichotomous Thinking
In statistics, dichotomous thinking or binary thinking is the process of seeing a discontinuity in the possible values that a p-value can take during null hypothesis significance testing: it is either above the significance threshold (usually 0.05) or below. When applying dichotomous thinking, a first p-value of 0.0499 will be interpreted the same as a p-value of 0.0001 (the null hypothesis is rejected) while a second p-value of 0.0501 will be interpreted the same as a p-value of 0.7 (the null hypothesis is accepted). The fact that first and second p-values are mathematically very close is thus completely disregarded and values of p are not considered as continuous but are interpreted dichotomously with respect to the significance threshold. A common measure of dichotomous thinking is the cliff effect. A reason to avoid dichotomous thinking is that p-values and other statistics naturally change from study to study due to random variation alone; decisions about refutation or support o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistics
Statistics (from German language, German: ''wikt:Statistik#German, Statistik'', "description of a State (polity), state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of statistical survey, surveys and experimental design, experiments.Dodge, Y. (2006) ''The Oxford Dictionary of Statistical Terms'', Oxford University Press. When census data cannot be collected, statisticians collect data by developing specific experiment designs and survey sample (statistics), samples. Representative sampling as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
P-value
In null-hypothesis significance testing, the ''p''-value is the probability of obtaining test results at least as extreme as the result actually observed, under the assumption that the null hypothesis is correct. A very small ''p''-value means that such an extreme observed outcome would be very unlikely under the null hypothesis. Reporting ''p''-values of statistical tests is common practice in academic publications of many quantitative fields. Since the precise meaning of ''p''-value is hard to grasp, misuse is widespread and has been a major topic in metascience. Basic concepts In statistics, every conjecture concerning the unknown probability distribution of a collection of random variables representing the observed data X in some study is called a ''statistical hypothesis''. If we state one hypothesis only and the aim of the statistical test is to see whether this hypothesis is tenable, but not to investigate other specific hypotheses, then such a test is called a null ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistical Hypothesis Testing
A statistical hypothesis test is a method of statistical inference used to decide whether the data at hand sufficiently support a particular hypothesis. Hypothesis testing allows us to make probabilistic statements about population parameters. History Early use While hypothesis testing was popularized early in the 20th century, early forms were used in the 1700s. The first use is credited to John Arbuthnot (1710), followed by Pierre-Simon Laplace (1770s), in analyzing the human sex ratio at birth; see . Modern origins and early controversy Modern significance testing is largely the product of Karl Pearson ( ''p''-value, Pearson's chi-squared test), William Sealy Gosset ( Student's t-distribution), and Ronald Fisher ("null hypothesis", analysis of variance, "significance test"), while hypothesis testing was developed by Jerzy Neyman and Egon Pearson (son of Karl). Ronald Fisher began his life in statistics as a Bayesian (Zabell 1992), but Fisher soon grew disenchanted with t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cliff Effect
In telecommunications, the (digital) cliff effect or brickwall effect is a sudden loss of digital signal reception. Unlike analog signals, which gradually fade when signal strength decreases or electromagnetic interference or multipath increases, a digital signal provides data which is either perfect or non-existent at the receiving end. It is named for a graph of reception quality versus signal quality, where the digital signal "falls off a cliff" instead of having a gradual rolloff. This is an example of an EXIT chart. The phenomenon is primarily seen in broadcasting, where signal strength is liable to vary, rather than in recorded media, which generally have a good signal. However, it may be seen in significantly damaged media, which is at the edge of readability. The term is also used in economics for an unrelated phenomenon. Broadcasting Digital television This effect can most easily be seen on digital television, including both satellite TV and over-the-air terrestria ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Splitting (psychology)
Splitting (also called black-and-white thinking or all-or-nothing thinking) is the failure in a person's thinking to bring together the dichotomy of both perceived positive and negative qualities of something into a cohesive, realistic whole. It is a common defense mechanism wherein the individual tends to think in extremes (e.g., an individual's actions and motivations are ''all'' good or ''all'' bad with no middle ground). This kind of dichotomous interpretation is contrasted by an acknowledgement of certain nuances known as "shades of gray". Splitting was first described by Ronald Fairbairn in his formulation of object relations theory; it begins as the inability of the infant to combine the fulfilling aspects of the parents (the good object) and their unresponsive aspects (the unsatisfying object) into the same individuals, instead seeing the good and bad as separate. In psychoanalytic theory this functions as a defense mechanism. Relationships Splitting creates instability i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Logic And Statistics
Logic is the study of correct reasoning. It includes both Mathematical logic, formal and informal logic. Formal logic is the science of Validity (logic), deductively valid inferences or of logical truths. It is a formal science investigating how conclusions follow from premises in a topic-neutral way. When used as a countable noun, the term "a logic" refers to a logical formal system that articulates a proof system. Formal logic contrasts with informal logic, which is associated with informal fallacies, critical thinking, and argumentation theory. While there is no general agreement on how formal and informal logic are to be distinguished, one prominent approach associates their difference with whether the studied arguments are expressed in Formal language, formal or Natural language, informal languages. Logic plays a central role in multiple fields, such as philosophy, mathematics, computer science, and linguistics. Logic studies arguments, which consist of a set of premises t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
