| D009010 |
Monte Carlo Method |
In statistics, a technique for numerically approximating the solution of a mathematical problem by studying the distribution of some random variable, often generated by a computer. The name alludes to the randomness characteristic of the games of chance played at the gambling casinos in Monte Carlo. (From Random House Unabridged Dictionary, 2d ed, 1993) |
Method, Monte Carlo |
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| D011336 |
Probability |
The study of chance processes or the relative frequency characterizing a chance process. |
Probabilities |
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| D012044 |
Regression Analysis |
Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. |
Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions |
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| D004812 |
Epidemiologic Methods |
Research techniques that focus on study designs and data gathering methods in human and animal populations. |
Epidemiologic Method,Epidemiological Methods,Methods, Epidemiologic,Epidemiological Method,Method, Epidemiologic,Method, Epidemiological,Methods, Epidemiological |
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| D006801 |
Humans |
Members of the species Homo sapiens. |
Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man |
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| D000704 |
Analysis of Variance |
A statistical technique that isolates and assesses the contributions of categorical independent variables to variation in the mean of a continuous dependent variable. |
ANOVA,Analysis, Variance,Variance Analysis,Analyses, Variance,Variance Analyses |
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| D015233 |
Models, Statistical |
Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc. |
Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model |
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