Results 201 to 210 of about 6,994,987 (257)
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Journal of Chemical Education, 1991
Computer simulations provide new insights into the correct application of statistical procedures to the small samples typical of the undergraduate laboratory.
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Computer simulations provide new insights into the correct application of statistical procedures to the small samples typical of the undergraduate laboratory.
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2004
Abstract Barclaycard ‘s principal tools for controlling credit risk are ‘Credit Scorecards ‘ and ‘Behaviour Scorecards ‘. These are linear models which predict the chance that a customer will continue to make regular repayments within, say, the next year. Usually these scorecards are built using large samples (e.g. 10,0(X) accounts).
Alan Lucas, Joanna Powell
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Abstract Barclaycard ‘s principal tools for controlling credit risk are ‘Credit Scorecards ‘ and ‘Behaviour Scorecards ‘. These are linear models which predict the chance that a customer will continue to make regular repayments within, say, the next year. Usually these scorecards are built using large samples (e.g. 10,0(X) accounts).
Alan Lucas, Joanna Powell
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Small Samples—New Experimental Results
Journal of the American Statistical Association, 1928(1928). Small Samples—New Experimental Results. Journal of the American Statistical Association: Vol. 23, No. 162, pp. 144-153.
W. A. Shewhart, F. W. Winters
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Small Samples in Contingency Tables
Biometrika, 1980SUMMARY The analysis of some contingency tables is based on hierarchical log linear models. Inferences about sets of parameters can then be made from conditional distributions. We discuss three ways of improving the asymptotic methods generally used in practice.
Cox, M. A. A., Plackett, R. L.
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Counseling Outcome Research and Evaluation, 2014
Single case designs (SCDs) and randomized small group (RSG) designs are two options for researchers who have limited resources and who would like to demonstrate the experimental effect of an interv...
Katherine E. Purswell, Dee C. Ray
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Single case designs (SCDs) and randomized small group (RSG) designs are two options for researchers who have limited resources and who would like to demonstrate the experimental effect of an interv...
Katherine E. Purswell, Dee C. Ray
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Journal of Educational Statistics, 1988
An approach for modifying the results of asymptotic theory to improve the performance of statistical procedures in small to moderate sample sizes is described in the context of hypothesis testing. The method is illustrated by a series of examples.
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An approach for modifying the results of asymptotic theory to improve the performance of statistical procedures in small to moderate sample sizes is described in the context of hypothesis testing. The method is illustrated by a series of examples.
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International Journal of Market Research, 2002
Discusses the dangers of drawing inferences from small samples of data, such as is typically done in qualitative research projects. The problem of ensuring representativeness is discussed: the dangers of convenience samples and the value of purposive sampling.
Timothy Bock, John Sergeant
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Discusses the dangers of drawing inferences from small samples of data, such as is typically done in qualitative research projects. The problem of ensuring representativeness is discussed: the dangers of convenience samples and the value of purposive sampling.
Timothy Bock, John Sergeant
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2015
In a number of application areas, such as materials and genomics, where one wishes to classify objects, sample sizes are often small owing to the expense or unavailability of data points. Many classifier design procedures work well with large samples but are ineffectual or, at best, problematic with small samples.
Lori A. Dalton, Edward R. Dougherty
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In a number of application areas, such as materials and genomics, where one wishes to classify objects, sample sizes are often small owing to the expense or unavailability of data points. Many classifier design procedures work well with large samples but are ineffectual or, at best, problematic with small samples.
Lori A. Dalton, Edward R. Dougherty
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1971
So far we have dealt with the methods of determining the reliability of statistics applicable only to what we have called large samples, and the reader ’s attention has repeatedly been drawn to this limitation. Now the smaller the samples, the more inaccurate become these methods.
T. G. Connolly, W. Sluckin
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So far we have dealt with the methods of determining the reliability of statistics applicable only to what we have called large samples, and the reader ’s attention has repeatedly been drawn to this limitation. Now the smaller the samples, the more inaccurate become these methods.
T. G. Connolly, W. Sluckin
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Small‐sample intervals for regression
Canadian Journal of Statistics, 1992AbstractFor the general linear regression model Y = Xη + e, we construct small‐sample exponentially tilted empirical confidence intervals for a linear parameter 6 = aTη and for nonlinear functions of η. The coverage error for the intervals is Op(1/n), as shown in Tingley and Field (1990).
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