
Review of Short Phrases and Links 
This Review contains major "Hypothesis Test" related terms, short phrases and links grouped together in the form of Encyclopedia article.
Definitions
 In a hypothesis test, a type I error occurs when the null hypothesis is rejected when it is in fact true; that is, H 0 is wrongly rejected.
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 In a hypothesis test, a type II error occurs when the null hypothesis H 0, is not rejected when it is in fact false.
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 To obtain a hypothesis test, the likelihood ratio, LR, is compared to its sampling distribution under the null hypothesis.
 Click OK in the TwoSample Test for Variances dialog to perform the hypothesis test.
 In statistics, the logrank test (sometimes called the Mantel–Cox test) is a hypothesis test to compare the survival distributions of two samples.
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 Suppose that we want to carry out a hypothesis test to see if the true mean discharge differs from 6.
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 Summary In any hypothesis test we are testing the evidence to see if it is sufficient to reject the null hypothesis.
 In a statistical hypothesis test, there are two types of incorrect conclusions that can be drawn.
 In this type of hypothesis test, you determine whether the data "fit" a particular distribution or not.
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 For more discussion about the meaning of a statistical hypothesis test, see Chapter 1.
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 Instead one needs to manually perform the hypothesis test using output from descriptive statistics.
 Although the hypothesis test indicates whether there is a linear relationship, it gives no indication of the strength of that relationship.
 Exploration of how likely it is that this difference is due to chance requires a hypothesis test, in this case the one sample ttest.
 We can also carry out a hypothesis test of the null hypothesis that the difference between the proportions is 0.
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 Derivation of the sampling distribution is the first step in calculating a confidence interval or carrying out a hypothesis test for a parameter.
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 Every hypothesis test requires the analyst to state a null hypothesis and an alternative hypothesis.
 Statistical hypothesis testing  A statistical hypothesis test is a method of making statistical decisions using experimental data.
 The alternative hypothesis, H 1, is a statement of what a statistical hypothesis test is set up to establish.
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 This is analogous to assumption or retaining H 0 in a statistical hypothesis test.
 ONESAMPLE PROCEDURES. Hypothesis test and confi dence interval for the mean of a Normal distribution with unknown variance.
 We consider exact confidence limits obtained from discrete data by inverting a hypothesis test based on a studentized test statistic.
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 A chisquare test is any statistical hypothesis test in which the test statistic has a chisquare distribution if the null hypothesis is true.
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 Type II Error In a hypothesis test, a type II error occurs when the null hypothesis H0, is not rejected when it is in fact false.
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 In other words, the power of a hypothesis test is the probability of not committing a type II error.
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 Power comparisons: For a hypothesis test, a type I error occurs if H 0 is rejected when it is true.
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 To conduct the hypothesis test, we require a random sample of observed data.
 H = jbtest(X) performs the JarqueBera test on the input data vector X and returns H, the result of the hypothesis test.
 The null hypothesis H? is an assumption about a population which may or may not be rejected as the result of a hypothesis test.
 Two types of errors can result from a hypothesis test.
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 You use a chisquare test (meaning the distribution for the hypothesis test is chisquare) to determine if there is a fit or not.
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 In the end, most folks summarize the result of a hypothesis test into one particular value  the pvalue.
 Critical value The critical value in an hypothesis test is the value of the test statistic beyond which we would reject the null hypothesis.
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 The critical region CR, or rejection region RR, is a set of values of the test statistic for which the null hypothesis is rejected in a hypothesis test.
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 Its value is used to decide whether or not the null hypothesis should be rejected in our hypothesis test.
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 The critical region of a hypothesis test is the set of all outcomes which, if they occur, will lead us to decide that there is a difference.
 A ttest is any statistical hypothesis test in which the test statistic follows a Student's t distribution if the null hypothesis is true.
 A null hypothesis is a hypothesis that is presumed true until a hypothesis test indicates otherwise.
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 The result of the hypothesis test is a Boolean value that is 0 when you do not reject the null hypothesis, and 1 when you do reject that hypothesis.
 The output above provides a statistical hypothesis test for the hypothesis that gender and employment category are independent of each other.
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 In this section we will show how Excel is used to conduct a hypothesis test about the difference between two population means.
 Large Sample Size (say, over 30): In this section you wish to know how Excel can be used to conduct a hypothesis test about a population mean.
 In regard to a hypothesis test in the linear regression, we have two approaches: confidence interval or test of significance.
 A t  test is any statistical hypothesis test in which the test statistic follows a Student's t distribution if the null hypothesis is true.
 A test of significance, also called a statistical hypothesis test, is a slightly different twist on the same mathematics used in the confidence interval.
 The significance level of a statistical hypothesis test is a fixed probability of wrongly rejecting the null hypothesis H 0, if it is in fact true.
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 The significance level is chosen prior to conducting the hypothesis test.
 Modify the P value and significance level to better understand how their relationship determines the decision for a hypothesis test.
Hypothesis Test
 The significance level of an hypothesis test is the chance that the test erroneously rejects the null hypothesis when the null hypothesis is true.
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 In a hypothesis test, comparison of the value of a test statistic with the appropriate critical value determines the result of the test.
 H = lillietest(X) performs the Lilliefors test on the input data vector X and returns H, the result of the hypothesis test.
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Categories
 Science > Mathematics > Statistics > Null Hypothesis
 Science > Mathematics > Statistics > Test Statistic
 Significance Level
 Alternative Hypothesis
 Science > Mathematics > Statistics > Confidence Interval

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