1. |
Graphical Display of Means |
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The American Statistician,
Volume 34,
Issue 4,
1980,
Page 195-199
HoraceP. Andrews,
RonaldD. Snee,
MargaretH. Sarner,
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摘要:
A graphical procedure for the display of treatment means that enables one to determine the statistical significance of the observed differences is presented. It is shown that the widely used least significant difference and honestly significant difference statistics can be used to construct plots in which any two means whose uncertainty intervals do not overlap are significantly different at the assigned probability level. It is argued that these plots, because of their straightforward decision rules, are more effective than those that show the observed means with standard errors or confidence limits. Several examples of the proposed displays are included to illustrate the procedure.
ISSN:0003-1305
DOI:10.1080/00031305.1980.10483028
出版商:Taylor & Francis Group
年代:1980
数据来源: Taylor
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2. |
Characteristics of Formulas and Data Used in the Allocation of Federal Funds |
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The American Statistician,
Volume 34,
Issue 4,
1980,
Page 200-211
MaríaElena González,
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摘要:
The formulas and data used for 13 federal programs that allocate funds to state and local areas are described. Suggestions for types of formulas and data appropriate for allocation of funds are made. Some recommendations in theReport on Statistics for Allocation of Fundspublished by the Office of Federal Statistical Policy and Standards are discussed. The possible effects of the formulas and data used in the allocation of funds for federal programs are examined in the light of the recommendations given in the report.
ISSN:0003-1305
DOI:10.1080/00031305.1980.10483029
出版商:Taylor & Francis Group
年代:1980
数据来源: Taylor
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3. |
The Interpretation of Regression Analysis Results in Sex and Race Discrimination Problems |
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The American Statistician,
Volume 34,
Issue 4,
1980,
Page 212-215
GeorgeP. McCabe,
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摘要:
Linear models are often used to quantify differentials between protected and unprotected groups on variables such as salary. Some consequences of model misspecification are examined. In addition, the effects of preferential selection on linear analysis results are studied.
ISSN:0003-1305
DOI:10.1080/00031305.1980.10483030
出版商:Taylor & Francis Group
年代:1980
数据来源: Taylor
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4. |
Population Marginal Means in the Linear Model: An Alternative to Least Squares Means |
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The American Statistician,
Volume 34,
Issue 4,
1980,
Page 216-221
S.R. Searle,
F.M. Speed,
G.A. Milliken,
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摘要:
The parameter concept in the termleast squares meanis defined and given the more meaningful namepopulation marginal mean;and its estimation is discussed.
ISSN:0003-1305
DOI:10.1080/00031305.1980.10483031
出版商:Taylor & Francis Group
年代:1980
数据来源: Taylor
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5. |
The Planning Stage in Statistical Reasoning |
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The American Statistician,
Volume 34,
Issue 4,
1980,
Page 222-226
NormanL. Chervany,
P.George Benson,
RajaK. Iyer,
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摘要:
An important step in the statistical problem-solving process is the selection of the appropriate statistical procedure for the real-world situation under analysis. A decision-tree term project has been found to be an effective teaching device to help MBA students understand this step. The project requires the students to construct a decision-tree structure, which, through a series of questions and responses, will lead from the statement of a statistical question to the appropriate sampling distribution to use in addressing the question.
ISSN:0003-1305
DOI:10.1080/00031305.1980.10483032
出版商:Taylor & Francis Group
年代:1980
数据来源: Taylor
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6. |
Sample Sizes in the Interval Estimation of the Correlation Coefficient |
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The American Statistician,
Volume 34,
Issue 4,
1980,
Page 227-228
Girma Wolde-Tsadik,
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摘要:
An expression is derived for the maximum length of the interval estimator of the correlation coefficient,p, under bivariate normal assumptions. The prespecification of this minimum attainable precision and the confidence level results in an expression for the sample size required. An approximate expression for the sample size is proposed and is numerically shown to be as good as or better than that based on the Fisher'sZtransformation.
ISSN:0003-1305
DOI:10.1080/00031305.1980.10483033
出版商:Taylor & Francis Group
年代:1980
数据来源: Taylor
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7. |
Comparative Analyses of Pretest-Posttest Research Designs |
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The American Statistician,
Volume 34,
Issue 4,
1980,
Page 229-232
DonnaR. Brogan,
MichaelH. Kutner,
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摘要:
Two common methods of analyzing data from a two-group pretest-posttest research design are (a) two-samplettest on the difference score between pretest and posttest and (b) repeated-measures/split-plot analysis of variance. The repeated-measures/split-plot analysis subsumes thettest analysis, although the former requires more assumptions to be satisfied. A numerical example is given to illustrate some of the equivalences of the two methods of analysis. The investigator should choose the method of analysis based on the research objective(s).
ISSN:0003-1305
DOI:10.1080/00031305.1980.10483034
出版商:Taylor & Francis Group
年代:1980
数据来源: Taylor
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8. |
Efficient Likelihood Estimators |
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The American Statistician,
Volume 34,
Issue 4,
1980,
Page 233-235
E.L. Lehmann,
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摘要:
IfX1, …,Xnare identically and independently distributed, then asnŕ ∞, there exists under suitable regularity conditions a sequence of solutions of the likelihood equation that is consistent and asymptotically efficient. However, this consistent solution is not necessarily the maximum likelihood estimate. Likelihood estimation should therefore emphasize the determination of a consistent sequence of solutions of the likelihood equations rather than maximizing the likelihood. The issues are illustrated on some examples.
ISSN:0003-1305
DOI:10.1080/00031305.1980.10483036
出版商:Taylor & Francis Group
年代:1980
数据来源: Taylor
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9. |
Accent on Teaching Materials |
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The American Statistician,
Volume 34,
Issue 4,
1980,
Page 236-237
HarryO. Posten,
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ISSN:0003-1305
DOI:10.1080/00031305.1980.10483037
出版商:Taylor & Francis Group
年代:1980
数据来源: Taylor
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10. |
Statistical Computing: History and Trends |
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The American Statistician,
Volume 34,
Issue 4,
1980,
Page 238-243
JohnM. Chambers,
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摘要:
The evolution of computers is currently in a period of rapid change, stimulated by radically cheaper and smaller devices for processing and memory. These changes are certain to provide major opportunities and challenges for the use of computers in statistics. This article looks at history and current trends, in both general computing and statistical computing, with the goal of identifying key features and requirements for the near future. A discussion of the S language developed at Bell Laboratories illustrates some program design principles that can make future work on statistical programs more effective and more valuable.
ISSN:0003-1305
DOI:10.1080/00031305.1980.10483038
出版商:Taylor & Francis Group
年代:1980
数据来源: Taylor
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