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The initial evaluation of the set of observations to see whether or not they appear to satisfy the hypotheses or assumptions of the methods to be used in their analysis. Techniques or methods which highlight the possible outliers, or, for instance, departures from normality, like a normal probability plot, are significant in this phase of an investigation.
The Null Hypothesis - H0: β 1 = 0 i.e. there is homoscedasticity errors and no heteroscedasticity exists The Alternative Hypothesis - H1: β 1 ≠ 0 i.e. there is no homoscedasti
Post stratification adjustmen t: One of the most often used population weighting adjustments used in the complex surveys, in which weights for the elements in a class are multiplie
Build-Rite construction has received favorable publicity from guest appearances on a public TV home improvement program. Public TV programming decisions seem to be unpredictable, s
Procedures for estimating the probability distributions without supposing any particular functional form. Constructing the histogram is perhaps the easiest example of such type of
Interior analysis is the term now and again applied to analysis carried out on the fitted model in regression problem. The basic target of such analyses is the identification of
properties of chebyshevs lemma
Behrens Fisher problem : The difficulty of testing for the equality of the means of the two normal distributions which do not have the equal variance. Various test statistics have
Graphical deception : Statistical graphics which are not as honest as they should be. It is relatively simple. To mislead the unwary with the graphical material. For instance, c
Marginal matching is the matching of the treatment groups in terms of means or other summary characteristics of matching variables. This has been shown to be almost as efficient a
The Null Hypothesis - H0: There is no first order autocorrelation The Alternative Hypothesis - H1: There is first order autocorrelation Durbin-Watson statistic = 1.98307
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