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Academic journal
Bayesian Analysis is an open-access peer-reviewed scientific journal covering theoretical and applied aspects of Bayesian methods. It is published by
Bayesian_Analysis_(journal)
Theory and paradigm of statistics
trials. More concretely, analysis in Bayesian methods codifies prior knowledge in the form of a prior distribution. Bayesian statistical methods use Bayes'
Bayesian_statistics
Method of statistical inference
mathematical statistics. Bayesian updating is particularly important in the dynamic analysis of a sequence of data. Bayesian inference has found application
Bayesian_inference
Type of sensitivity analysis
robust Bayesian analysis, also called Bayesian sensitivity analysis, is a type of sensitivity analysis applied to the outcome from Bayesian inference
Robust_Bayesian_analysis
Interpretation of probability
data analysis using what is now known as Bayesian inference. Mathematician Pierre-Simon Laplace pioneered and popularized what is now called Bayesian probability
Bayesian_probability
Method of statistical analysis
Bayesian linear regression is a type of conditional modeling in which the mean of one variable is described by a linear combination of other variables
Bayesian_linear_regression
redirect targets Approximate Bayesian computation – Computational method in Bayesian statistics Bayesian Analysis (journal) Bayesian approaches to brain function –
List of things named after Thomas Bayes
List_of_things_named_after_Thomas_Bayes
Statistical method
Debajyoti; Dey, Dipak K. (September 1997). "Semiparametric Bayesian Analysis of Survival Data". Journal of the American Statistical Association. 92 (439): 1195–1212
Bayesian_survival_analysis
Free and open-source statistical program
ANOVA, Regression, Variances) BSTS: Bayesian take on linear Gaussian state space models suitable for time series analysis. Circular Statistics: Basic methods
JASP
Experimental design framework
Bayesian experimental design provides a general probability-theoretical framework from which other theories on experimental design can be derived. It is
Bayesian_experimental_design
Sequential model-based optimization of expensive black-box functions
Bayesian optimization is a sequential model-based strategy for optimizing black-box objective functions that are expensive to evaluate. It is commonly
Bayesian_optimization
The International Society for Bayesian Analysis (ISBA) is a society with the goal of promoting Bayesian analysis for solving problems in the sciences and
International Society for Bayesian Analysis
International_Society_for_Bayesian_Analysis
Computational method in Bayesian statistics
Approximate Bayesian computation (ABC) constitutes a class of computational methods rooted in Bayesian statistics that can be used to estimate the posterior
Approximate Bayesian computation
Approximate_Bayesian_computation
Probabilistic graphical representation of causal relationships
A Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents a
Bayesian_network
Statistical method that summarizes and/or integrates data from multiple sources
been executed using Bayesian methods, mixed linear models and meta-regression approaches. Specifying a Bayesian network meta-analysis model involves writing
Meta-analysis
Explaining the brain's abilities through statistical principles
Bayesian approaches to brain function investigate the capacity of the nervous system to operate in situations of uncertainty in a fashion that is close
Bayesian approaches to brain function
Bayesian_approaches_to_brain_function
Probabilistic theory of knowledge
Bayesian epistemology is a formal approach to various topics in epistemology that has its roots in Thomas Bayes' work in the field of probability theory
Bayesian_epistemology
Statistical method for molecular phylogenetics
Bayesian inference of phylogeny combines the information in the prior and in the data likelihood to create the so-called posterior probability of trees
Bayesian inference in phylogeny
Bayesian_inference_in_phylogeny
Set of statistical processes for estimating the relationships among variables
accommodating various types of missing data, nonparametric regression, Bayesian methods for regression, regression in which the predictor variables are
Regression_analysis
Statistical estimation method
In statistics and econometrics, Bayesian vector autoregression (BVAR) uses Bayesian methods to estimate a vector autoregression (VAR) model. BVAR differs
Bayesian vector autoregression
Bayesian_vector_autoregression
Criterion for model selection
In statistics, the Bayesian information criterion (BIC) or Schwarz information criterion (also SIC, SBC, SBIC) is a criterion for model selection among
Bayesian information criterion
Bayesian_information_criterion
Distribution of an uncertain quantity
dominates the information contained in the data being analyzed. The Bayesian analysis combines the information contained in the prior with that extracted
Prior_probability
Branch of econometrics
Bayesian econometrics is a branch of econometrics which applies Bayesian principles to economic modelling. Bayesianism is based on a degree-of-belief interpretation
Bayesian_econometrics
Statistical technique used for feature selection
Bayesian structural time series (BSTS) model is a statistical technique used for feature selection, time series forecasting, nowcasting, inferring causal
Bayesian structural time series
Bayesian_structural_time_series
Ratio of competing statistical models
compared to its linear approximation. The Bayes factor can be thought of as a Bayesian analog to the likelihood-ratio test, although it uses the integrated (i
Bayes_factor
Mathematical rule for inverting probabilities
by Pierre-Simon Laplace. One of Bayes' theorem's many applications is Bayesian inference, an approach to statistical inference, where it is used to invert
Bayes'_theorem
Game theory concept
In game theory, a Bayesian game is a strategic decision-making model which assumes players have incomplete information. Players may hold private information
Bayesian_game
Experimental design that is optimal with respect to some statistical criterion
Design and Analysis of Experiments. Handbook of Statistics. pp. 977–1006. DasGupta, A. "Review of Optimal Bayesian Designs". Design and Analysis of Experiments
Optimal_experimental_design
first complete analysis of Bayesian Inference for many statistical problems. Importance: Includes a large body of research on Bayesian analysis for outlier
List of publications in statistics
List_of_publications_in_statistics
Statistics and machine learning technique
Andrew (2018). "Using Stacking to Average Bayesian Predictive Distributions (with Discussion)". Bayesian Analysis. 13 (3): 917–1007. arXiv:1704.02030. doi:10
Ensemble_learning
Collection of statistical models
Analysis of variance (ANOVA) is a family of statistical methods used to compare the means of two or more groups by analyzing variance. Specifically, ANOVA
Analysis_of_variance
Class of statistical tests
tested against the null hypothesis that it is normally distributed. In Bayesian statistics, one does not "test normality" per se, but rather computes the
Normality_test
Type of statistical model
Hyperparameter Mixed-design analysis of variance Multiscale modeling Random effects model Nonlinear mixed-effects model Bayesian hierarchical modeling Restricted
Multilevel_model
Denial of the scientific consensus on climate change
popularity of conspiracy theories of presidential assassination: A Bayesian analysis". Journal of Personality and Social Psychology. 37 (5): 637–644. doi:10
Climate_change_denial
Fienberg, (2006) When did Bayesian Inference become "Bayesian"? Archived 2014-09-10 at the Wayback Machine Bayesian Analysis, 1 (1), 1–40. See page 5.
History_of_statistics
Survey-based statistical technique
unsuitable for market segmentation studies. With newer hierarchical Bayesian analysis techniques, individual-level utilities may be estimated that provide
Conjoint_analysis
Method of data analysis
Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data
Principal_component_analysis
Probabilistic problem-solving algorithm
density function analysis of radiative forcing. Monte Carlo methods are used in various fields of computational biology, for example for Bayesian inference in
Monte_Carlo_method
popularity of conspiracy theories of presidential assassination: A Bayesian analysis". Journal of Personality and Social Psychology. 37 (5): 637–644. doi:10
Psychology of climate change denial
Psychology_of_climate_change_denial
Method of statistical inference
Objective Bayesian Analysis". Bayesian Analysis. 1 (3): 385–402. doi:10.1214/06-ba115. In listing the competing definitions of "objective" Bayesian analysis, "A
Statistical_hypothesis_test
Branch of statistics focusing on spatial data sets
calculate its posterior. High-dimensional Bayesian geostatistics refers to Bayesian modeling and analysis for geostatistical data when the number of
Geostatistics
Approximation method in statistics
ISBN 9783642201929. Park, Trevor; Casella, George (2008). "The Bayesian Lasso". Journal of the American Statistical Association. 103 (482): 681–686. doi:10
Least_squares
Type of heuristic technique
bounds established for UCB algorithms to Bayesian regret bounds for Thompson sampling or unify regret analysis across both these algorithms and many classes
Thompson_sampling
Study of uncertainty in the output of a mathematical model or system
1137/130936233. Sudret, B. (2008). "Global sensitivity analysis using polynomial chaos expansions". Bayesian Networks in Dependability]. 93 (7): 964–979. doi:10
Sensitivity_analysis
Probabilistic classification algorithm
quite well in many complex real-world situations. In 2004, an analysis of the Bayesian classification problem showed that there are sound theoretical
Naive_Bayes_classifier
French statistician (born 1961)
from 2006 to 2009. He was president of the International Society for Bayesian Analysis in 2008. In 2016 he was joint program chair of the AIStats conference
Christian_Robert
Statistical model written in multiple levels
Bayesian hierarchical modelling is a statistical model written in multiple levels (hierarchical form) that estimates the posterior distribution of model
Bayesian hierarchical modeling
Bayesian_hierarchical_modeling
Type of statistical inference
and type II errors. As a point of reference, the complement to this in Bayesian statistics is the minimum Bayes risk criterion. Because of the reliance
Frequentist_inference
Range to estimate an unknown parameter
calculated interval, which is instead associated with the credible interval in Bayesian inference. The confidence level instead reflects the long-run reliability
Confidence_interval
Probability distribution
)} it generalizes the normal distribution and also arises in the Bayesian analysis of data from a normal family as a compound distribution when marginalizing
Student's_t-distribution
Process of using data analysis for predicting population data from sample data
alia's Statistics. Moore et al. (2015). Gelman A. et al. (2013). Bayesian Data Analysis (Chapman & Hall). Peirce (1877-1878) Peirce (1883) Freedman, Pisani
Statistical_inference
Bayesian history matching is a statistical method for calibrating complex computer models. The equations inside many scientific computer models contain
Bayesian_history_matching
Concept in medicine referring to design of clinical trials
nature of adaptive trials inherently suggests the use of Bayesian statistical analysis. Bayesian statistics inherently address updating information such
Adaptive_design_(medicine)
Grouping a set of objects by similarity
Cluster analysis, or clustering, is a data analysis technique aimed at partitioning a set of objects into groups such that objects within the same group
Cluster_analysis
Statistical method
Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved
Factor_analysis
Subset of artificial intelligence
and learning. Bayesian networks that model sequences of variables, like speech signals or protein sequences, are called dynamic Bayesian networks. Generalisations
Machine_learning
Branch of statistics
Accelerated failure time model – Parametric model in survival analysis Bayesian survival analysis – Statistical method Cell survival curve – Curve in radiobiology
Survival_analysis
Problem in statistical estimation
numbers. The problem can be approached using either frequentist inference or Bayesian inference, leading to different results. Estimating the population maximum
German_tank_problem
Breed of sheep
Trends for Milk Production of Blond-Faced Latxa Sheep Using Bayesian Analysis". Journal of Dairy Science. 79 (12): 2268–77. doi:10.3168/jds.S0022-0302(96)76604-3
Latxa
Term in statistical hypothesis testing
Power analysis is primarily a frequentist statistics tool. In Bayesian statistics, hypothesis testing of the type used in classical power analysis is not
Power_(statistics)
Application of statistical methods to marketing processes
In marketing, Bayesian inference allows for decision making and market research evaluation under uncertainty and with limited data. The communication between
Bayesian inference in marketing
Bayesian_inference_in_marketing
In Bayesian probability theory
likelihood function that has been integrated over the parameter space. In Bayesian statistics, it represents the probability of generating the observed sample
Marginal_likelihood
American statistician
Hal S.; Dunson, David B.; Vehtari, Aki; Rubin, Donald B. (2013). Bayesian Data Analysis, Third Edition. New York, New York: Chapman and Hall. doi:10.1201/b16018
David_Dunson
Function related to statistics and probability theory
maximum) gives an indication of the estimate's precision. In contrast, in Bayesian statistics, the estimate of interest is the converse of the likelihood
Likelihood_function
Statistical modeling method
of the error term. Bayesian linear regression applies the framework of Bayesian statistics to linear regression. (See also Bayesian multivariate linear
Linear_regression
American statistician
Minneapolis, Minnesota) is an American statistician best known for his work on Bayesian statistics and decision theory. He won the COPSS Presidents' Award, one
James_O._Berger
Mathematical relation assigning a probability event to a cost
EMS Press Berger, James O. (1985). Statistical decision theory and Bayesian Analysis (2nd ed.). New York: Springer-Verlag. Bibcode:1985sdtb.book.....B
Loss_function
Use of statistical measurement systems to study human behavior in a social environment
theory Bayesian statistics Stochastic process Latent class model Cluster analysis Multidimensional scaling Classification analysis Cohort analysis Social
Social_statistics
Extinct genus of Early Miocene ape from Egypt
secondary bayesian analysis tree based on craniodental and DNA data is given below: A simplified version of the standard non-clock bayesian analysis tree is
Masripithecus
Use of statistics in psychology
include psychometrics, factor analysis, experimental designs, and Bayesian statistics. The article also discusses journals in the same field. Psychometrics
Psychological_statistics
Overview of and topical guide to machine learning
Vapnik–Chervonenkis theory Variable-order Bayesian network Variable kernel density estimation Variable rules analysis Variational message passing Varimax rotation
Outline_of_machine_learning
Concepts underlying statistical methods
on the analysis and interpretation of data, and some of these contrasts have been subject to centuries of debate. Examples include the Bayesian inference
Foundations_of_statistics
Study of collection and analysis of data
Research Journal. 3 (3): 223–229. doi:10.3102/00028312003003223. JSTOR 1161806. S2CID 145725524. Agresti, Alan; Hichcock, David B. (2005). "Bayesian Inference
Statistics
International Journal of Forecasting Journal of Time Series Analysis The following journals are considered open access: Bayesian Analysis Brazilian Journal of Probability
List_of_statistics_journals
pp. 361–371. Benson, Noah C; Winawer, Jonathan (December 2018). "Bayesian analysis of retinotopic maps". eLife. 7 e40224. doi:10.7554/elife.40224. PMC 6340702
Data_analysis
Feature of artificial neural networks
to the infinite width limit of Bayesian neural networks, and to the distribution over functions realized by non-Bayesian neural networks after random initialization
Large width limits of neural networks
Large_width_limits_of_neural_networks
Indian-American statistician
known for his research contributions to Bayesian hierarchical modeling and inference for spatial data analysis. He is Professor of Biostatistics and Senior
Sudipto_Banerjee
Statistical property of collections of time series data
for cointegration with two unknown breaks are also available. Several Bayesian methods have been proposed to compute the posterior distribution of the
Cointegration
Interval bounded by an upper and a lower limit statistics
confidence intervals (a frequentist method) and credible intervals (a Bayesian method). Less common forms include likelihood intervals, fiducial intervals
Interval_estimation
Formal information theory restatement of Occam's Razor
Minimum message length (MML) is a Bayesian information-theoretic method for statistical model comparison and selection. It provides a formal information
Minimum_message_length
Estimator for quality of a statistical model
and Bayesian inference. AIC, though, can be used to do statistical inference without relying on either the frequentist paradigm or the Bayesian paradigm:
Akaike_information_criterion
Statistical model
2013.04.029. Banerjee, Sudipto (2017). "High-dimensional Bayesian Geostatistics". Bayesian Analysis. 12 (2): 583–614. doi:10.1214/17-BA1056R. PMC 5790125
Gaussian_process
Simultaneous observation and analysis of more than one outcome variable
distribution. The Inverse-Wishart distribution is important in Bayesian inference, for example in Bayesian multivariate linear regression. Additionally, Hotelling's
Multivariate_statistics
distribution is effectively used as a joint prior distribution in Bayesian analysis, especially when the likelihood is not from the location-scale family
Generalized multivariate log-gamma distribution
Generalized_multivariate_log-gamma_distribution
Method in statistics
the class of probabilistic numerical methods. Bayesian quadrature views numerical integration as a Bayesian inference task, where function evaluations are
Bayesian_quadrature
Generalized version of the Akaike information criterion
(2013). Bayesian Data Analysis (Third ed.). Chapman and Hall/CRC. ISBN 978-1-4398-4095-5. Watanabe, Sumio (2013). "A Widely Applicable Bayesian Information
Watanabe–Akaike information criterion
Watanabe–Akaike_information_criterion
Bayesian statistics textbook by Richard McElreath
Statistical Rethinking: A Bayesian Course with Examples in R and Stan is an applied Bayesian statistics textbook by Richard McElreath. A second edition
Statistical_Rethinking
Statistical model validation technique
intuitively define shrinkage estimators like the (adaptive) lasso and Bayesian / ridge regression. Click on the lasso for an example. Suppose we choose
Cross-validation_(statistics)
Overview of and topical guide to statistics
model Online machine learning Cross-validation (statistics) Recursive Bayesian estimation Kalman filter Particle filter Moving average SQL Statistical
Outline_of_statistics
Python package
ArviZ (/ˈɑːrvɪz/ AR-vees) is a Python package for exploratory analysis of Bayesian models. It is specifically designed to work with the output of probabilistic
ArviZ
Method of estimating the parameters of a statistical model, given observations
have normal distributions with the same variance. From the perspective of Bayesian inference, MLE is generally equivalent to maximum a posteriori (MAP) estimation
Maximum_likelihood_estimation
Science of characterizing uncertainties
(2009-03-01). "Modularization in Bayesian analysis, with emphasis on analysis of computer models". Bayesian Analysis. 4 (1). Institute of Mathematical
Uncertainty_quantification
BEAST 2 is a cross-platform program for Bayesian analysis of molecular sequences. Using MCMC, it estimates rooted, timed phylogenies using a range of
BEAST_2
Class of statistical models
method on many statistical computing packages. Other approaches, including Bayesian regression and least squares fitting to variance stabilized responses,
Generalized_linear_model
Transmission of a pathogen between different species
but not for host shifts. This highlights how Bayesian inferences in models can be used for CST analysis.[citation needed] Mathematical modelling of infectious
Cross-species_transmission
Task of selecting a statistical model from a set of candidate models
the Akaike information criterion and (ii) the Bayes factor and/or the Bayesian information criterion (which to some extent approximates the Bayes factor)
Model_selection
Sequence of data points over time
Nonlinear mixed-effects modeling Dynamic time warping Dynamic Bayesian network Time-frequency analysis techniques: Fast Fourier transform Continuous wavelet transform
Time_series
Statistical model containing both fixed effects and random effects
Bürkner, Paul-Christian (2017). "brms : An R Package for Bayesian Multilevel Models Using Stan". Journal of Statistical Software. 80 (1). doi:10.18637/jss.v080
Mixed_model
British statistician and geneticist (1919–2000)
American Statistical Association. Biography portal Cornwall portal Analysis of variance Bayesian experimental design Biostatistics ("Biometry" or "Biometrics")
Oscar_Kempthorne
Hypothesis in neuroscience
used in Bayesian approaches to brain function and some approaches to artificial intelligence; it is formally related to variational Bayesian methods.
Free_energy_principle
BAYESIAN ANALYSIS-JOURNAL
BAYESIAN ANALYSIS-JOURNAL
Girl/Female
Hindu
Analysis
Boy/Male
Muslim
Boy/Male
Indian
Girl/Female
Hindu
Analysis
Girl/Female
Hindu, Indian
Analyses
Girl/Female
Latin
Graced with God's bounty.
Girl/Female
Muslim
To walk with pride
Girl/Female
Hindu
Analysis
Girl/Female
Indian
Analysis
Girl/Female
Tamil
Sameksha | ஸமேகà¯à®·à®¾
Analysis
Sameksha | ஸமேகà¯à®·à®¾
Girl/Female
Tamil
Sumiksha | ஸà¯à®®à¯€à®•à¯à®·à®¾Â
Close inspection, A review, Analysis
Sumiksha | ஸà¯à®®à¯€à®•à¯à®·à®¾Â
Girl/Female
Muslim
Analysis
Girl/Female
Arabic, Muslim
To Walk with Pride
Boy/Male
Hindu, Indian
Analytic Brain
Girl/Female
Tamil
Samiksha | ஸமீகà¯à®·à®¾
Analysis
Samiksha | ஸமீகà¯à®·à®¾
Girl/Female
Hindu
Close inspection, A review, Analysis
Surname or Lastname
English
English : habitational name from places in Lincolnshire and Nottinghamshire called Winthorpe. The former is named with the Old English personal name or byname Wine, meaning ‘friend’, + Old Norse þorp ‘settlement’. In the latter the first element is a contracted form of the Old English personal name Wigmund, composed of the elements wÄ«g ‘war’ + mund ‘protection’, or the Old Norse equivalent, VÃgmundr.John Winthrop (1588–1649) was the first governor of the Massachusetts Bay Colony. He kept a detailed journal, an invaluable source for historians. He was born into a family of Suffolk, England, gentry whose fortunes were founded by his grandfather Adam Winthrop (d. 1562) of Lavenham. In 1544 the latter acquired a 500-acre estate that had been part of the monastery of Bury St. Edmunds. John Winthrop emigrated from Groton, Suffolk, England, to Salem, MA, in 1630 because of Charles I’s anti-Puritan policies. By the time of his death he had had four wives and 16 children, the most notable of whom was his son John (1606–76), a scientist and governor of CT. His descendants were prominent in politics and science, including John Winthrop (1714–79), an astronomer, and Robert Winthrop (1809–94), a senator and speaker of the House of Representatives.
Girl/Female
Tamil
Sameeksha | ஸமீகà¯à®·à®¾Â
Analysis
Sameeksha | ஸமீகà¯à®·à®¾Â
Surname or Lastname
English
English : patronymic from the personal name Will.George Willis is recorded in Boston, MA, in the 1630s. Nathianel Willis, born in Boston in 1780, and his son Nathaniel Parker Willis, born in Portland, ME, in 1806, were both prominent journalists.
Girl/Female
Indian, Telugu
Review; Analysis
BAYESIAN ANALYSIS-JOURNAL
BAYESIAN ANALYSIS-JOURNAL
Girl/Female
Arabic, Muslim
Full Moon of the Women
Boy/Male
Hindu, Indian
Graceful
Boy/Male
Teutonic American
Of holy fame.
Girl/Female
Tamil
Vrajabala | வà¯à®°à®œà®ªà®¾à®²à®¾
Girl from Mathura and its neighborhood
Boy/Male
American, Australian, British, English
Poet; English and American Place Name; Variant of the English County Name Devon
Girl/Female
Gujarati, Hindu, Indian, Kannada, Malayalam, Marathi, Sanskrit, Tamil, Telugu
Graceful; Goddess Laxmi
Boy/Male
British, English, Irish
A Prince; Hero
Female
English
English name derived from the Scottish place name Morvern, from Gaelic Mhorbhairne, MORVEN means "the big gap."
Girl/Female
Hindu
Happiness
Boy/Male
Welsh
Legendary son of Taran.
BAYESIAN ANALYSIS-JOURNAL
BAYESIAN ANALYSIS-JOURNAL
BAYESIAN ANALYSIS-JOURNAL
BAYESIAN ANALYSIS-JOURNAL
BAYESIAN ANALYSIS-JOURNAL
pl.
of Analysis
a.
Of or pertaining to analysis; resolving into elements or constituent parts; as, an analytical experiment; analytic reasoning; -- opposed to synthetic.
n.
One who analyzes; formerly, one skilled in algebraical geometry; now commonly, one skilled in chemical analysis.
n.
A process by which reaction occurs in the presence of certain agents which were formerly believed to exert an influence by mere contact. It is now believed that such reactions are attended with the formation of an intermediate compound or compounds, so that by alternate composition and decomposition the agent is apparenty left unchanged; as, the catalysis of making ether from alcohol by means of sulphuric acid; or catalysis in the action of soluble ferments (as diastase, or ptyalin) on starch.
n.
Synthesis as opposed to analysis.
n.
That which is educed, as by analysis.
n.
A brief, methodical illustration of the principles of a science. In this sense it is nearly synonymous with synopsis.
n.
A resolution of anything, whether an object of the senses or of the intellect, into its constituent or original elements; an examination of the component parts of a subject, each separately, as the words which compose a sentence, the tones of a tune, or the simple propositions which enter into an argument. It is opposed to synthesis.
n.
A journey or expedition up from the coast, like that of the younger Cyrus into Central Asia, described by Xenophon in his work called "The Anabasis."
n.
The science of analysis.
n.
Chemical analysis.
n.
Paralysis, complete or partial. See Paralysis.
n.
The science of blowpipe analysis.
n.
Analysis into primary or elemental parts.
n.
Alt. of Analyser
n.
The tracing of things to their source, and the resolving of knowledge into its original principles.
n.
A syllabus, or table of the principal heads of a discourse, disposed in their natural order.
n.
The resolving of problems by reducing the conditions that are in them to equations.
n.
The separation of a compound substance, by chemical processes, into its constituents, with a view to ascertain either (a) what elements it contains, or (b) how much of each element is present. The former is called qualitative, and the latter quantitative analysis.
n.
The process of ascertaining the name of a species, or its place in a system of classification, by means of an analytical table or key.