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Unformatted text preview: Lecture XXIII In general there are two kinds of hypotheses: one concerns the form of the probability distribution (i.e. is the random variable normally distributed) and the second concerns parameters of a distribution function (i.e. what is the mean of a distribution). The second kind of distribution is the traditional stuff of econometrics. We may be interested in testing whether the effect of income on consumption is greater than one, or whether the effect of price on the level consumed is equal to zero. The second kind of hypothesis is termed a simple hypothesis. Under this scenario, we test the value of a parameter against a single alternative. The first kind of hypothesis (whether the effect of income on consumption is greater than one) is termed a composite hypothesis. Implicit in this test is several alternative values. Hypothesis testing involves the comparison between two competing hypothesis, or conjectures. The null hypothesis, denoted H , is sometimes referred to as the maintained hypothesis. The alternative hypothesis is the hypothesis that will be accepted if the null hypothesis is rejected. The general notion of the hypothesis test is that we collect a sample of data X 1 , X n . This sample is a multivariate random variable, E n . (The text refers to this as an element of a Euclidean space). If the multivariate random variable is contained in space R , we reject the null hypothesis. Alternatively, if the random variable is in the complement of the space R , we fail to reject the null hypothesis. Mathematically, The set R is called the region of rejection or the critical region of the test....
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This note was uploaded on 07/18/2011 for the course AEB 6933 taught by Professor Carriker during the Fall '09 term at University of Florida.
 Fall '09
 CARRIKER

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