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Statistical parameter
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151	PROBABILITY MODELS FOR ECONOMIC DECISIONS Chapter 2: Discrete Random Variables In this chapter, we focus on one simple example, but in the context of this example we develop most of the technical concepts of probability Add to Reading List Source URL: home.uchicago.edu Language: English - Date: 2002-10-07 12:40:48 Randomness Probability theory Statistical theory Probability distribution Expected value Random variable Variable Parameter Uncertainty Mathematics Statistics Probability and statistics
152	Tests of Equivalence and Confidence Intervals for Effect Sizes Point or sharp null hypotheses specify that a parameter has a particular value -for example, (or  Add to Reading List Source URL: core.ecu.edu Language: English Design of experiments Clinical research Statistical tests Confidence interval Bioequivalence Statistical power Effect size Analysis of variance Statistical hypothesis testing Statistics Hypothesis testing Statistical inference
153	Package ‘usl’ February 20, 2015 Type Package Title Analyze System Scalability with the Universal Scalability Law VersionDate Add to Reading List Source URL: cran.r-project.org Language: English Neil J. Gunther Data analysis Scalability Confidence interval Regression analysis Parameter Subroutine Bootstrapping Statistics Statistical inference Econometrics
154	Making Inferences About Parameters Parametric statistical inference may take the form of: 1. Estimation: on the basis of sample data we estimate the value of some parameter of the population from which the sample was Add to Reading List Source URL: core.ecu.edu Language: English - Date: 2014-08-03 13:18:42 Statistical theory Estimation theory Statistical tests Statistical hypothesis testing Null hypothesis Statistical power Estimator Sample size determination Normal distribution Statistics Statistical inference Hypothesis testing
155	Confidence Intervals for Proportions If one has a relatively large sample (large enough to use a normal approximation of the binomial parameter p), then one can construct a confidence interval about one’s estimate of Add to Reading List Source URL: core.ecu.edu Language: English - Date: 2015-02-19 21:24:52 Interval Normal distribution Tolerance interval Binomial proportion confidence interval Statistics Statistical inference Confidence interval
156	M ODEL S ELECTION AND R EGULARIZATION PARAMETER C HOICE R EGULARIZATION M ETHODS FOR H IGH D IMENSIONAL L EARNING Francesca Odone and Lorenzo Rosasco - Add to Reading List Source URL: lcsl.mit.edu Language: English - Date: 2014-07-02 03:10:16 Statistical classification Mathematics Summability methods Learning Regularization Tikhonov regularization Support vector machine Generalization error Solid modeling Statistics Machine learning Quantum field theory
157	Combining Active Sampling with Parameter Estimation and Prediction in Single Networks Joseph J. Pfeiffer III Jennifer Neville Department of Computer Science, Purdue University, West Lafayette, IN Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2013-05-17 16:26:10 Graph theory Maximum likelihood Statistical theory Graph Parameter Mathematics Estimation theory Statistics
158	Package ‘BMA’ February 19, 2015 VersionDateTitle Bayesian Model Averaging Author Adrian Raftery <>, Jennifer Hoeting, Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2015-02-19 03:23:58 Estimation theory Bayesian inference Statistical models Dummy variable Parameter Logistic regression Economic model Linear regression Bayes factor Statistics Regression analysis Econometrics
159	Biogeosciences, 9, 3983–3998, 2012 www.biogeosciences.netdoi:bg © Author(sCC Attribution 3.0 License. Biogeosciences Add to Reading List Source URL: www.biogeosciences.net Language: English - Date: 2014-12-03 14:15:48 Statistical theory Environmental science Parameter Greenhouse gas Credible interval Regression analysis Statistical inference Swat-CUP Statistics Bayesian statistics Econometrics
160	Some Very Basic Concepts Reviewed in the First Chapter of Howell. Variables A variable is a quantity that can take on different values. A constant is a quantity that is always of the same value. Discrete variable Add to Reading List Source URL: core.ecu.edu Language: English - Date: 2013-09-04 22:10:27 Statistical inference Data analysis Logical syntax Sample mean and sample covariance Descriptive statistics Parameter Mean Statistic Expected value Statistics Summary statistics Variables

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