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Make objective decisions about the validity of the hypotheses.

Q: What does hypothesis testing through statistical procedures enable researchers to do?

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I think you are asking: What is hypothesis testing in the field of statistics. See: http://en.wikipedia.org/wiki/Statistical_hypothesis_testing

A hypothesis is the first step in running a statistical test (t-test, chi-square test, etc.) A NULL HYPOTHESIS is the probability that what you are testing does NOT occur. An ALTERNATIVE HYPOTHESIS is the probability that what you are testing DOES occur.

A non-directional research hypothesis is a kind of hypothesis that is used in testing statistical significance. It states that there is no difference between variables.

The difference between the null hypothesis and the alternative hypothesis are on the sense of the tests. In statistical inference, the null hypothesis should be in a positive sense such in a sense, you are testing a hypothesis you are probably sure of. In other words, the null hypothesis must be the hypothesis you are almost sure of. Just an important note, that when you are doing a tests, you are testing if a certain event probably occurs at certain level of significance. The alternative hypothesis is the opposite one.

Statistical tests compare the observed (or more extreme) values against what would be expected if the null hypothesis were true. If the probability of the observation is high you would retain the null hypothesis, if the probability is low you reject the null hypothesis. The thresholds for high or low probability are usually set arbitrarily at 5%, 1% etc. Strictly speaking, when rejecting the null hypothesis, you do not accept the alternative hypothesis because it is possible that neither are true and it is the model itself that is wrong.

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In fact, any statistical relationship in a sample can be interpreted in two ways: ... The purpose of null hypothesis testing is simply to help researchers decide ... the null hypothesis in favour of the alternative hypothesisâ€”concluding that there is a ...

A statistical estimate of the population parameter.

I think you are asking: What is hypothesis testing in the field of statistics. See: http://en.wikipedia.org/wiki/Statistical_hypothesis_testing

A hypothesis is the first step in running a statistical test (t-test, chi-square test, etc.) A NULL HYPOTHESIS is the probability that what you are testing does NOT occur. An ALTERNATIVE HYPOTHESIS is the probability that what you are testing DOES occur.

A non-directional research hypothesis is a kind of hypothesis that is used in testing statistical significance. It states that there is no difference between variables.

Herman J. Loether has written: 'Inferential statistics for sociologists' -- subject(s): Sampling (Statistics), Sociology, Statistical hypothesis testing, Statistical methods 'Descriptive and inferential statistics' -- subject(s): Sampling (Statistics), Sociology, Statistical hypothesis testing, Statistical methods 'Descriptive statistics for sociologists' -- subject(s): Sociology, Statistical methods

Lehmann has written: 'Nonparametrics : statistical methods based on ranks' -- subject(s): Nonparametric statistics, Statistical hypothesis testing

Ning-Zhong Shi has written: 'Statistical hypothesis testing'

A statistical hypothesis test will usually be performed by inductively comparing results of experiments or observations. The number or amount of comparisons will generally dictate the statistical test to use. The researcher is basically making a statement and assuming that it is either correct (the hypothesis - H1) or assuming that it is incorrect (the null hypothesis - H0) and testing that assumption within a predetermined significance level - the alpha.

Mary LaBrake has written: 'Tests for differences' -- subject(s): Statistical hypothesis testing

Kurt Stange has written: 'Bayes-Verfahren' -- subject(s): Bayesian statistical decision theory, Estimation theory, Statistical hypothesis testing

Bhaskar Kumar Ghosh has written: 'Sequential tests of statistical hypotheses' -- subject(s): Statistical hypothesis testing, Sequential analysis