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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
Topics referred to by the same term
Component analysis may refer to one of several topics in statistics: Principal component analysis, a technique that converts a set of observations of
Component_analysis
Signal processing computational method
In signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents.
Independent component analysis
Independent_component_analysis
Component analysis is the analysis of two or more independent variables which comprise a treatment modality. It is also known as a dismantling study. The
Component analysis (statistics)
Component_analysis_(statistics)
Multivariate statistical technique
field of multivariate statistics, kernel principal component analysis (kernel PCA) is an extension of principal component analysis (PCA) using techniques
Kernel principal component analysis
Kernel_principal_component_analysis
Multilinear extension of principal component analysis
Multilinear principal component analysis (MPCA) is a multilinear extension of principal component analysis (PCA) that is used to analyze M-way arrays,
Multilinear principal component analysis
Multilinear_principal_component_analysis
Approach of analyzing data sets in statistics
In statistics, exploratory data analysis (EDA) or exploratory analytics is an approach of analyzing data sets to summarize their main characteristics
Exploratory_data_analysis
Statistical term
In statistics, path analysis is used to describe the directed dependencies among a set of variables. This includes models equivalent to any form of multiple
Path_analysis_(statistics)
Simultaneous observation and analysis of more than one outcome variable
Multivariate statistics is a subdivision of statistics encompassing the simultaneous observation and analysis of more than one outcome variable, i.e.,
Multivariate_statistics
Study of collection and analysis of data
Statistics (from German: Statistik, orig. "description of a state, a country") is the discipline that concerns the collection, organization, analysis
Statistics
Grouping a set of objects by similarity
when neural networks implement a form of Principal Component Analysis or Independent Component Analysis. A "clustering" is essentially a set of such clusters
Cluster_analysis
Method of data analysis
Robust Principal Component Analysis (RPCA) is a modification of the widely used statistical procedure of principal component analysis (PCA) which works
Robust principal component analysis
Robust_principal_component_analysis
Process of understanding a complex topic or substance
language in general by breaking language down into component parts for analysis. Core areas of analysis include theory, phonetics (the production and perception
Analysis
Statistics concept
In statistics and optimization, errors and residuals are two closely related and easily confused measures of the deviation of an observed value of an element
Errors_and_residuals
Process of using data analysis for predicting population data from sample data
Following Kolmogorov's work in the 1950s, advanced statistics uses approximation theory and functional analysis to quantify the error of approximation. In this
Statistical_inference
Diagnostic plot in multivariate statistics
In multivariate statistics, a scree plot is a line plot of the eigenvalues of factors or principal components in an analysis. The scree plot is used to
Scree_plot
Multivariate statistical technique
Principal Component Analysis (sPCA) is a multivariate statistical technique that complements the traditional Principal Component Analysis (PCA) by incorporating
Spatial Analysis of Principal Components
Spatial_Analysis_of_Principal_Components
Statistical method for investigating the dominant modes of variation of functional data
Functional principal component analysis (FPCA) is a statistical method for investigating the dominant modes of variation of functional data. Using this
Functional principal component analysis
Functional_principal_component_analysis
Data analysis technique
In statistics, multiple correspondence analysis (MCA) is a data analysis technique for nominal categorical data, used to detect and represent underlying
Multiple correspondence analysis
Multiple_correspondence_analysis
Sampling from a population which can be partitioned into subpopulations
In statistics, stratified sampling is a method of sampling from a population which can be partitioned into subpopulations. In statistical surveys, when
Stratified_sampling
Method used in statistics, pattern recognition, and other fields
LDA method. LDA is also closely related to principal component analysis (PCA) and factor analysis in that they both look for linear combinations of variables
Linear_discriminant_analysis
Statistical method
"Principal component analysis vs. exploratory factor analysis" (PDF). SUGI 30 Proceedings. Retrieved 5 April 2012. SAS Statistics. "Principal Components Analysis"
Factor_analysis
Collection of statistical models
analysis of variance to data analysis was published in 1921, Studies in Crop Variation I. This divided the variation of a time series into components
Analysis_of_variance
In statistics, kernel-independent component analysis (kernel ICA) is an efficient algorithm for independent component analysis which estimates source
Kernel-independent component analysis
Kernel-independent_component_analysis
Periodicity computation method
"successive spectral analysis" and the result a "least-squares periodogram". He generalized this method to account for any systematic components beyond a simple
Least-squares spectral analysis
Least-squares_spectral_analysis
Type of statistics
robust statistics, and are now the preferred solution, though they can be quite involved to calculate. Gelman et al. in Bayesian Data Analysis (2004)
Robust_statistics
Overview of and topical guide to statistics
overview of and topical guide to statistics: Statistics is a field of inquiry that studies the collection, analysis, interpretation, and presentation
Outline_of_statistics
Statistical model validation technique
deemed truly informative. A recent development in medical statistics is its use in meta-analysis. It forms the basis of the validation statistic, Vn which
Cross-validation_(statistics)
Statistical method
analysis, also known as Horn's parallel analysis, is a statistical method used to determine the number of components to keep in a principal component
Parallel_analysis
Set of statistical processes for estimating the relationships among variables
In statistical modeling, regression analysis is a statistical method for estimating the relationship between a dependent variable (often called the outcome
Regression_analysis
Sequence of data points over time
measurements. Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics
Time_series
Approximation method in statistics
In regression analysis, least squares is a method to determine the best-fit model by minimizing the sum of the squared residuals—the differences between
Least_squares
Fisher discriminant analysis Kernel methods Kernel principal component analysis Kernel regression Kernel smoother Kernel (statistics) Khmaladze transformation
List_of_statistics_articles
Diagnostic plot of binary classifier ability
can be generalized to multiple classes) at varying threshold values. ROC analysis is commonly applied in the assessment of diagnostic test performance in
Receiver operating characteristic
Receiver_operating_characteristic
Field of geometry and statistics
data analysis comprises geometric aspects of image analysis, pattern analysis, and shape analysis, and the approach of multivariate statistics, which
Geometric_data_analysis
Method of statistical inference
technique in statistics, and especially in mathematical statistics. Bayesian updating is particularly important in the dynamic analysis of a sequence
Bayesian_inference
analysis can be divided into descriptive statistics, exploratory data analysis (EDA), and confirmatory data analysis (CDA). EDA focuses on discovering new
Data_analysis
Nonparametric spectral estimation method
of time series into a sum of components, each having a meaningful interpretation. The name "singular spectrum analysis" relates to the spectrum of eigenvalues
Singular_spectrum_analysis
Unit of information
values that conveys information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may
Data
Number of values in the final calculation of a statistic that are free to vary
degrees-of-freedom of the corresponding component vectors. The three-population example above is an example of one-way Analysis of Variance. The model, or treatment
Degrees of freedom (statistics)
Degrees_of_freedom_(statistics)
Bayesian analysis for outlier problems, variance components, linear models and multivariate statistics. Theory of Probability Author: Bruno de Finetti
List of publications in statistics
List_of_publications_in_statistics
Branch of statistics
techniques that are commonly used in statistics include mathematical analysis, linear algebra, stochastic analysis, differential equations, and measure
Mathematical_statistics
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)
Measure of the joint variability
factor model being derived from principal component analysis. Algorithms for calculating covariance Analysis of covariance Autocovariance Covariance function
Covariance
Covariance and correlation
{}^{\rm {H}}} denotes Hermitian transposition. In time series analysis and statistics, the cross-correlation of a pair of random process is the correlation
Cross-correlation
Statistical distribution for dependence between random variables
reliability analysis of complex systems of machine components with competing failure modes. Copulas are being used for warranty data analysis in which the
Copula_(statistics)
Pearson's chi-squared test and principal component analysis. In 1911 he founded the world's first university statistics department at University College London
History_of_statistics
Concept in inferential statistics
Cumming, Geoff (2012). Understanding The New Statistics: Effect Sizes, Confidence Intervals, and Meta-Analysis. New York, USA: Routledge. pp. 27–28. Krzywinski
Statistical_significance
British polymath (1890–1962)
investment, and also pioneered linkage analysis and gene mapping. On the other hand, as the founder of modern statistics, Fisher made countless contributions
Ronald_Fisher
Statistical method for analysing climate data
Directional component analysis (DCA) is a statistical method used in climate science for identifying representative patterns of variability in space-time
Directional component analysis
Directional_component_analysis
Statistical measure of the magnitude of a phenomenon
concerning effect sizes is referred to as estimation statistics. Effect size is an essential component in the evaluation of the strength of a statistical
Effect_size
Statistical property
(2012-07-26). "Breusch Pagan Test for Heteroscedasticity". Basic Statistics and Data Analysis. Retrieved 2020-11-28. Pryce, Gwilym. "Heteroscedasticity: Testing
Homoscedasticity and heteroscedasticity
Homoscedasticity_and_heteroscedasticity
Statistical method
Design and Analysis of Ecological Experiments. CRC Press. ISBN 0412035618. Ch13, p300 Rice, John. Mathematical Statistics and Data Analysis (2 ed.). p
Bootstrapping_(statistics)
Signal representation
electronics, control systems engineering, and statistics, the frequency domain refers to the analysis of mathematical functions or signals with respect
Frequency_domain
Statistical hypothesis test
(also chi-square or χ2 test) is a statistical hypothesis test used in the analysis of contingency tables when the sample sizes are large. In simpler terms
Chi-squared_test
Class of statistical survival models
stroke occurring, or, changing the material from which a manufactured component is constructed, may double its hazard rate for failure. Other types of
Proportional_hazards_model
Value that appears most often in a set of data
In statistics, the mode is the value that appears most often in a set of data values. If X is a discrete random variable, the mode is the value x at which
Mode_(statistics)
Statistic for rank correlation
concordance and discordance also appear in other areas of statistics, like the Rand index in cluster analysis. Let ( x 1 , y 1 ) , . . . , ( x n , y n ) {\displaystyle
Kendall rank correlation coefficient
Kendall_rank_correlation_coefficient
Experimental design in statistics
; Hunter, W. G.; Hunter, J. S. (1978). Statistics for Experimenters: An Introduction to Design, Data Analysis and Model Building. Wiley. ISBN 978-0-471-09315-2
Factorial_experiment
Branch of statistics
Survival analysis is a branch of statistics for analyzing the expected duration of time until one event occurs, such as death in biological organisms and
Survival_analysis
Estimator for quality of a statistical model
(1978), "Further analysis of the data by Akaike's information criterion and the finite corrections", Communications in Statistics - Theory and Methods
Akaike_information_criterion
Kth smallest value in a statistical sample
analyze order statistics of random samples from a continuous distribution, the cumulative distribution function is used to reduce the analysis to the case
Order_statistic
N-th root of the product of n numbers
time been used to calculate financial indices (the averaging is over the components of the index). For example, in the past the FT 30 index used a geometric
Geometric_mean
Distinction between nominal, ordinal, interval and ratio variables
variable, interval scale statistics such as means can meaningfully be used on ordinal scale variables. Statistical analysis software such as SPSS requires
Level_of_measurement
Complete set of items that share at least one property in common
In statistics, a population is a set of similar items which is of interest for some question or experiment. A statistical population can be a group of
Statistical_population
Statistical modeling method
two-stage procedure first reduces the predictor variables using principal component analysis, and then uses the reduced variables in an OLS regression fit. While
Linear_regression
Branch of statistics mathematics
Functional data analysis (FDA) is a branch of statistics that analyses data providing information about curves, surfaces or anything else varying over
Functional_data_analysis
Data analysis method
component analysis (L1-PCA) is a general method for multivariate data analysis. L1-PCA is often preferred over standard L2-norm principal component analysis
L1-norm principal component analysis
L1-norm_principal_component_analysis
Probabilistic problem-solving algorithm
Software package for simulating nuclear processes Morris method – Analysis in applied statistics Multilevel Monte Carlo method Quasi-Monte Carlo method – Numerical
Monte_Carlo_method
Application of statistical techniques to biological systems
collection and analysis of experimental and observational data, and the interpretation of the results. It is closely related to medical statistics. Biostatistical
Biostatistics
Mathematical relation assigning a probability event to a cost
terms from several levels of the hierarchy[clarification needed]. In statistics, typically a loss function is used for parameter estimation, and the event
Loss_function
Position that there is no relationship between two phenomena
warrant for their position Counternull Estimation statistics – Data analysis approach in frequentist statistics Likelihood-ratio test – Statistical test that
Null_hypothesis
Class of statistical models
In statistics, a generalized linear model (GLM) is a flexible generalization of ordinary linear regression. The GLM generalizes linear regression by allowing
Generalized_linear_model
Type of statistics
nonparametric statistics. Even when a data analysis draws its main conclusions using inferential statistics, descriptive statistics are generally also presented. For
Descriptive_statistics
Non-parametric method for testing whether samples originate from the same distribution
Wayne W. (1990). "Kruskal–Wallis one-way analysis of variance by ranks". Applied Nonparametric Statistics (2nd ed.). Boston: PWS-Kent. pp. 226–234. ISBN 0-534-91976-6
Kruskal–Wallis_test
Function of the observed sample results
interpreted, increase the rigor of the conclusions drawn from data". In statistics, every conjecture concerning the unknown probability distribution of a
P-value
Statistics concept
In statistics, polynomial regression is a form of regression analysis in which the relationship between the independent variable x and the dependent variable
Polynomial_regression
Probability distribution
ISBN 9780852641378. Jackman, S. (2009). Bayesian Analysis for the Social Sciences. Wiley Series in Probability and Statistics. Wiley. p. 507. doi:10.1002/9780470686621
Student's_t-distribution
Method of estimating the parameters of a statistical model, given observations
Values. Springer Series in Statistics. doi:10.1007/978-1-4471-3675-0. ISBN 978-1-84996-874-4. ISSN 0172-7397. Statistical Analysis of Extreme Values. 2007
Maximum_likelihood_estimation
Bias in causal inference
in an analysis. If measures or manipulations of core constructs are confounded (i.e. operational or procedural confounds exist), subgroup analysis may not
Confounding
Function related to statistics and probability theory
which corresponds to the density component, the likelihood function for an observation from the continuous component can be dealt with in the manner shown
Likelihood_function
Correlation of a signal with a time-shifted copy of itself, as a function of shift
_{XX}(0)=\sigma ^{2}.} It is common practice in some disciplines (e.g. statistics and time series analysis) to normalize the autocovariance function to get a time-dependent
Autocorrelation
Measure of covariance of components of a random vector
additional properties of covariance matrices). This is called principal component analysis (PCA) and the Karhunen–Loève transform (KL-transform). The covariance
Covariance_matrix
Measure of linear correlation
} This decorrelation is related to principal components analysis for multivariate data. R's statistics base-package implements the correlation coefficient
Pearson correlation coefficient
Pearson_correlation_coefficient
Condition in which the value of a measurement or observation is only partially known
numerator. Data analysis Detection limit Imputation (statistics) Inverse probability weighting Sampling bias Saturation arithmetic Survival analysis Winsorising
Censoring_(statistics)
Statistics is the theory and application of mathematics to the scientific method including hypothesis generation, experimental design, sampling, data collection
Founders_of_statistics
Type of average of a collection of numbers
In mathematics and statistics, the arithmetic mean ( /ˌærɪθˈmɛtɪk/ arr-ith-MET-ik), arithmetic average, or just the mean or average is the sum of a collection
Arithmetic_mean
Type of chart
Beniger, James R.; Robyn, Dorothy L. (1978), "Quantitative Graphics in Statistics: A Brief History", The American Statistician, 32 (1), Taylor & Francis
Bar_chart
Type of stochastic process
higher n {\displaystyle n} -point statistics are assumed to be stationary in the spatial domain. In time series analysis and stochastic processes, stationarizing
Stationary_process
Statistical measure of how far values spread from their average
In probability theory and statistics, variance is a measure of dispersion, meaning it is a measure of how far a set of numbers are spread out from their
Variance
Family of statistical methods based on sampling of available data
Monographs on Statistics & Applied Probability Verbyla, D. (1986). "Potential prediction bias in regression and discriminant analysis". Canadian Journal
Resampling_(statistics)
Concept in statistics
In descriptive statistics, the range of a set of data is the size or width of the narrowest interval which contains all the data. It is calculated as the
Range_(statistics)
Method of statistical inference
opinion polls to medical studies) are based on statistics. Some writers have stated that statistical analysis of this kind allows for thinking clearly about
Statistical_hypothesis_test
Statistics is the mathematical science involving the collection, analysis and interpretation of data. A number of specialties have evolved to apply statistical
List of fields of application of statistics
List_of_fields_of_application_of_statistics
Statistical hypothesis test
important role in the analysis of variance (ANOVA). F-test of analysis of variance (ANOVA) follows three assumptions Normality (statistics) Homogeneity of variance
F-test
General linear model that blends ANOVA and regression
Analysis of covariance (ANCOVA) is a general linear model that blends ANOVA and regression. ANCOVA evaluates whether the means of a dependent variable
Analysis_of_covariance
Type of statistics
the associated box plot. Entries in an analysis of variance table can also be regarded as summary statistics. Common measures of location, or central
Summary_statistics
Statistical model for count data
In statistics, Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression
Poisson_regression
Statistical model
In econometrics, a random effects model, also called a variance components model, is a statistical model where the model effects are random variables.
Random_effects_model
American statistician and econometrician (1895–1973)
T-squared distribution in statistics. He also developed and named the principal component analysis method widely used in finance, statistics and computer science
Harold_Hotelling
COMPONENT ANALYSIS-STATISTICS
COMPONENT ANALYSIS-STATISTICS
Boy/Male
Muslim
Competent
Girl/Female
Indian
Competent
Girl/Female
Indian
Analysis
Girl/Female
Hindu, Indian
Analyses
Girl/Female
Latin
Graced with God's bounty.
Girl/Female
Indian, Telugu
Review; Analysis
Girl/Female
Muslim
Analysis
Girl/Female
Hindu
Analysis
Girl/Female
Tamil
Sameeksha | ஸமீகà¯à®·à®¾Â
Analysis
Sameeksha | ஸமீகà¯à®·à®¾Â
Boy/Male
Anglo Saxon
Competent.
Girl/Female
Hindu
Analysis
Boy/Male
Arabic, Muslim
Competent
Girl/Female
Hindu
Analysis
Boy/Male
Arabic, Muslim
Competent
Boy/Male
Arabic, Muslim
Competent
Boy/Male
Arabic, Muslim
Competent
Girl/Female
Tamil
Samiksha | ஸமீகà¯à®·à®¾
Analysis
Samiksha | ஸமீகà¯à®·à®¾
Girl/Female
Tamil
Sameksha | ஸமேகà¯à®·à®¾
Analysis
Sameksha | ஸமேகà¯à®·à®¾
Girl/Female
Indian
Competent.
Boy/Male
Hindi
Competent.
COMPONENT ANALYSIS-STATISTICS
COMPONENT ANALYSIS-STATISTICS
Male
Russian
(ÐÌлик) Short form of Russian Aleksandr, ALIK means "defender."
Boy/Male
Hindu
One who delights
Male
Chamoru
, father.
Male
Hebrew
Variant spelling of Hebrew Eythan, EITAN means "enduring, long-lived."Â
Boy/Male
Muslim
Appropriate, Correct
Girl/Female
Australian, Greek
Theresa; Harvest
Boy/Male
Arabic, Muslim
Name of Son of Imam Muslim (RA)
Male
Dutch
, holy name.
Girl/Female
German, Polish
Ruler of an Enclosure; Home Ruler; Female Version of Henry
Boy/Male
Indian
Holy words
COMPONENT ANALYSIS-STATISTICS
COMPONENT ANALYSIS-STATISTICS
COMPONENT ANALYSIS-STATISTICS
COMPONENT ANALYSIS-STATISTICS
COMPONENT ANALYSIS-STATISTICS
n.
That which is educed, as by analysis.
n.
One who analyzes; formerly, one skilled in algebraical geometry; now commonly, one skilled in chemical 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.
n.
Paralysis, complete or partial. See Paralysis.
v. t.
Serving, or helping, to form; composing; constituting; constituent.
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.
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.
Alt. of Analyser
n.
A brief, methodical illustration of the principles of a science. In this sense it is nearly synonymous with synopsis.
n.
A constituent part; an ingredient.
a.
Of or pertaining to analysis; resolving into elements or constituent parts; as, an analytical experiment; analytic reasoning; -- opposed to synthetic.
n.
Analysis into primary or elemental parts.
pl.
of Analysis
n.
The principal component part of a thing.
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.
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.
The science of analysis.
n.
Synthesis as opposed to analysis.
n.
Chemical analysis.
n.
The science of blowpipe analysis.