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/*******************************************************************************
 * Copyright (c) 2010 Haifeng Li
 *   
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *  
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 *******************************************************************************/

/**
 * Statistical hypothesis tests. A statistical hypothesis test is a method
 * of making decisions using data, whether from a controlled experiment or
 * an observational study (not controlled). In statistics, a result is called
 * statistically significant if it is unlikely to have occurred by chance alone,
 * according to a pre-determined threshold probability, the significance level.
 * 

* Hypothesis testing is sometimes called confirmatory data analysis, in * contrast to exploratory data analysis. In frequency probability, these * decisions are almost always made using null-hypothesis tests (i.e., tests * that answer the question Assuming that the null hypothesis is true, what * is the probability of observing a value for the test statistic that is at * least as extreme as the value that was actually observed?) One use of * hypothesis testing is deciding whether experimental results contain enough * information to cast doubt on conventional wisdom. *

* A result that was found to be statistically significant is also called a * positive result; conversely, a result that is not unlikely under the null * hypothesis is called a negative result or a null result. *

* Statistical hypothesis testing is a key technique of frequentist statistical * inference. The Bayesian approach to hypothesis testing is to base rejection * of the hypothesis on the posterior probability. Other approaches to reaching * a decision based on data are available via decision theory and optimal * decisions. * * @author Haifeng Li */ package smile.stat.hypothesis;





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