**See also:** Statistical State Status Static Statistics Stature Statute Statutory Statement Stationary Stat Stately Stated Statue Stationery Compact Thesis Mission Socioeconomic Nation Descriptive Does

**1.** A *Statistical model* is** a mathematical representation (or mathematical model) of observed data.** When data analysts apply various *Statistical model*s to the data they are investigating, they are able to understand and interpret the information more strategically.

Statistical, Strong, Strategically

**2.** Cox (1994), Section 1.1; Bernardo and Smith (1994), Chapter 4] a *Statistical model* is a set of probability distributions on the sample spaceS

Section, Smith, Statistical, Set, Sample, Spaces

**3.** A parameterized *Statistical model* is a parameter set together with a function P: →P(S), which assigns to each parameter point θ ∈ a probability distribution Pθ on S.

Statistical, Set

**4.** In probability theory a *Statistical model* is** a mathematical model that reflects a set of statistical assumptions with regards to the process governing the generation of sample data from a larger population.** The *Statistical model* is thus an idealized form of …

Statistical, Strong, Set, Sample

**5.** In simple terms, *Statistical model*ing is** a simplified, mathematically-formalized way to approximate reality (i**.e.** what generates your data)** and optionally to** make predictions from this approximation**

Simple, Statistical, Strong, Simplified

**6.** The *Statistical model* is the mathematical equation that is used

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**7.** *Statistical model* A *Statistical model*** embodies a set of assumptions concerning the generation of the observed data, and similar data from a larger population.** A model represents, often in considerably idealized form, the data-generating process.

Statistical, Strong, Set, Similar

**8.** How to choose a *Statistical model*

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**9.** It is a very interesting illustration of how one would choose a *Statistical model*

Statistical

**10.** Building a *Statistical model* involves constructing a mathematical description of some real-world phenomena that accounts for the uncertainty and/or randomness involved in that system

Statistical, Some, System

**11.** A *Statistical model* is** a type of mathematical model that comprises of the assumptions undertaken to describe the data generation process.** Let us focus on the two highlighted terms above: Type of mathematical model? *Statistical model* is non-deterministic unlike other mathematical models where variables have specific values.

Statistical, Strong, Specific

**12.** A *Statistical model* is** a probability distribution constructed to support analysis of data.** They differ from standard mathematical models in that they are non-deterministic

Statistical, Strong, Support, Standard

**13.** The choice of a *Statistical model* can also be guided** by the shape of the relationships between the dependent and explanatory variables.** A graphical exploration of these relationships may be very useful

Statistical, Strong, Shape

**14.** A *Statistical model* is a family of probability distributions, the central problem of statistical inference being to identify which member of the family generated the data currently of interest

Statistical

**15.** The *Statistical model* of grain growth is able to predict the effect of Zener drag on the grain size distribution evolution and on grain growth kinetics [1, 2]

Statistical, Size

**16.** *Statistical model*: a formal representation for a class of processes that allows a means of analyzing results from experimental studies, such as the Poisson model or the general linear model; it need not propose a process literally interpretable in the context of the individual case.

Statistical, Studies, Such

**17.** A *Statistical model* on another hand needs a supercomputer to run a million observation with thousand parameters

Statistical, Supercomputer

**18.** Differences between Machine Learning and *Statistical model*ing: Given the flavor of difference in output of these two approaches, let us understand the difference in the two paradigms, even though both do almost similar job :

Statistical, Similar

**19.** A *Statistical model* is a combination of inferences based on collected data and population understanding used to predict information in an idealized form

Statistical

**20.** **Methodology:** *Statistical model* We generate our Statistical Risk Assessment by identifying historical instances of mass killing, discerning patterns that distinguished countries that experienced mass killing from others, and then applying that model to the latest publicly available data to estimate the likelihood of a new mass killing in each of

Strong, Statistical

**21.** A *Statistical model* for the genetic origin of allometric scaling laws in biology

Statistical, Scaling

**22.** From the Cambridge English Corpus In order to explain legislative success, this article presents a *Statistical model* estimating both …

Success, Statistical

**23.** *Statistical model*s “All models are wrong, but some are useful” -George E

Statistical, Some

**24.** Other articles where *Statistical model* is discussed: nuclear model: …second group, called strong-interaction, or *Statistical model*s, the main assumption is that the protons and neutrons are mutually coupled to each other and behave cooperatively in a way that reflects the short-ranged strong nuclear force between them

Statistical, Second, Strong, Short

**25.** There are *Statistical model* that are robust to outlier like a Tree-based models but it will limit the possibility to try other models

Statistical

**26.** This will allow us to try more number of *Statistical model*

Statistical

**27.** This paper addresses two closely related questions, "What is a *Statistical model*?" and "What is a parameter?" The notions that a model must "make sense," and that a parameter must "have a well-defined meaning" are deeply ingrained in applied statistical work, reasonably well understood at an instinctive level, but absent from most formal theories of modelling and inference

Statistical, Sense

**28.** In a couple of lectures the basic notion of a *Statistical model* is described

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**29.** Emphasis is placed on R’s framework for *Statistical model*ing.

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**30.** Researchers have developed a new *Statistical model* that predicts which cities are more likely to become infectious disease hotspots, based both on interconnectivity between cities and the idea

Statistical

**31.** An example of a *Statistical model* is the apparent dependence of the transmissibility of influenza on temperature and humidity; studies done with guinea pigs have shown that the probability that a guinea pig gets infected by an infected cage-mate is significantly related to temperature and humidity (in a non-linear way).

Statistical, Studies, Shown, Significantly

**32.** The new functionality implemented in Version 5 allows Users to easily create a *Statistical model* to find anomalies in data containing a large number of dimension values

Statistical

**33.** If the Fisher information matrix is positive definite for all θ, then the corresponding *Statistical model* is said to be regular; otherwise, the *Statistical model* is said to be singular

Statistical, Said, Singular

**34.** Examples of singular *Statistical model*s include the following: normal mixtures, binomial mixtures, multinomial mixtures, Bayesian networks, neural networks, radial basis functions, hidden Markov models

Singular, Statistical

**35.** A *Statistical model* is a set of mathematical equations which describe the behavior of an object of study in terms of random variables and their associated probability distributions.

Statistical, Set, Study

**36.** In this lecture, I show which types of *Statistical model*s should be used when; the most important decision concerns the explanatory variables: When these are

Show, Statistical, Should

**37.** Methods of *Statistical model* Estimation examines the most important and popular methods used to estimate parameters for *Statistical model*s and provide informative model summary statistics

Statistical, Summary, Statistics

**38.** Designed for R users, the book is also ideal for anyone wanting to better understand the algorithms used for *Statistical model* fitting.

Statistical

**39.** Regression is the most popular *Statistical model* for predicting demand

Statistical

**40.** A *Statistical model* is used to describe the total loss, S (in kwacha), experienced in a certain computer manufacturing company over a period of one year due to mal- …

Statistical

**41.** A *Statistical model* is a set ${\mathcal S}$ of probability models, this is, a set of probability measures/distributions on the sample space $\Omega$

Statistical, Set, Sample, Space

**42.** In a *Statistical model*, the parameters and the

Statistical

**43.** This paper addresses two closely related questions, "What is a *Statistical model*?" and "What is a parameter?" The notions that a model must "make sense," and that a parameter must "have a well-defined meaning" are deeply ingrained in applied statistical work, reasonably well understood at an instinctive level, but absent from most formal theories of modelling and inference.

Statistical, Sense

**44.** *Statistical model* Analysis The Wolfram Language's symbolic architecture makes possible a uniquely convenient approach to working with *Statistical model*s

Statistical, Symbolic

**STATISTICAL MODEL**