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1 
A comparison of the performance of several solutions to the BehrensFisher problemKuzmak, Barbara Rose January 2010 (has links)
Typescript (photocopy). / Digitized by Kansas Correctional Industries / Department: Statistics.

2 
A new class of hypothesis tests which maximize average powerBegum, Nelufa, 1967 January 2003 (has links)
Abstract not available

3 
Testing hypotheses using unweighted meansPark, Byung S. 03 January 2002 (has links)
Testing main effects and interaction effects in factorial designs are basic content
in statistics textbooks and widely used in various fields. In balanced designs there
is general agreement on the appropriate main effect and interaction sums of
squares and these are typically displayed in an analysis of variance (ANOVA). A
number of methods for analyzing unbalanced designs have been developed, but in
general they do not lead to unique results. For example, in SAS one can get three
different main effect sums of squares in an unbalanced design. I, If these results
are viewed from the theory of the general linear model, then it is typically the case
that the different sums of squares all lead to Ftests, but they are testing different
linear hypotheses. In particular, if one clearly specifies the linear hypothesis being
tested, then linear model theory leads to one unique deviation sum of squares. One
exception to this statement is an ANOVA, called an unweighted means ANOVA
(UANOVA) introduced by Yates (1934). The deviation sum of squares in a
UNANOVA typically does not lead to an Ftest and hence does not reduce to a
usual deviation sum of squares for some linear hypothesis.
The UANOVA tests have been suggested by several writers as an alternative to
the usual tests. Almost all of these results are limited to the oneway model or a
twoway model with interaction, and hence the UANOVA procedure is not
available for a general linear model. This thesis generalizes the UANOVA test
prescribed in the twoway model with interaction to a general linear model. In
addition, the properties of the test are investigated. It is found, similar to the usual
test, that computation of the UANOVA test statistic does not depend on how the
linear hypothesis is formulated. It is also shown that the numerator of the
UANOVA test is like a linear combination of independent chisquared random
variables as opposed to a single chisquared random variable in the usual test. In
addition we show how the Imhof (1961) paper can be used to determine critical
values, pvalues and power for the UANOVA test. Comparisons with the usual
test are also included. It is found that neither test is more powerful than the other.
Even so, for most circumstances our general recommendation is that the usual test
is probably superior to the UANOVA test. / Graduation date: 2002

4 
Null hypothesis significance testing history, criticisms and aleternatives /Denis, J. Daniel. January 1999 (has links)
Thesis (M.A.)York University, 1999. Graduate Programme in Psychology. / Typescript. Includes bibliographical references (leaves 161176). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://wwwlib.umi.com/cr/yorku/fullcit?pMQ59127.

5 
The power of the KolmogorovSmirnov testSchultz, Rodney Edward, 1941 January 1972 (has links)
No description available.

6 
Beraming en toetsing in meervoudige binimiaal en normaalveranderingspuntproblemeVan Wyk, Jacob Lodewyk 08 May 2014 (has links)
D.Phil. (Statistics) / We often wish to determine whether observations occurring in a natural time sequence are from the same distribution or whether changes in distribution have taken place at certain points in time. These time points are called change points. We study tests of the null hypothesis of no change versus the alternative hypothesis of changes in parameter at unknown change points, as well as point and interval estimation of the change points. For univariate observations we distinguish between two cases. In the one case we consider observations having known, but unequal, variances. In the second case each observation has a variance which is a function of the unknown mean. In the first case we develop graphical procedures which can be used for the detection, as well as for point and interval estimation, of the change points. The method which we develop in the second case can be used for observations from any distribution, provided a suitable variance stabilizing transformation exists. Binomially distributed observations can be accommodated in both of these settings...

7 
Some contributions to asymptotic theory on hypothesis testing when the model is misspecified /Jeng, TianTzer January 1987 (has links)
No description available.

8 
Statistical methods for performance evaluation and their applications /Li, Longzhuang, January 2002 (has links)
Thesis (Ph. D.)University of MissouriColumbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 154170). Also available on the Internet.

9 
Statistical methods for performance evaluation and their applicationsLi, Longzhuang, January 2002 (has links)
Thesis (Ph. D.)University of MissouriColumbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 154170). Also available on the Internet.

10 
Estimating statistically significant differences between a pair of beta distributionsLakshminarayan, Krishnan January 2010 (has links)
Typescript (photocopy). / Digitized by Kansas Correctional Industries

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