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Confidence interval based parameter estimation--a new SOCR applet and activity.

Christou N, Dinov ID - PLoS ONE (2011)

Bottom Line: The SOCR confidence interval applet enables the user to empirically explore and investigate the effects of the confidence-level, the sample-size and parameter of interest on the corresponding confidence interval.Two applications of the new interval estimation computational library are presented.The first one is a simulation of confidence interval estimating the US unemployment rate and the second application demonstrates the computations of point and interval estimates of hippocampal surface complexity for Alzheimers disease patients, mild cognitive impairment subjects and asymptomatic controls.

View Article: PubMed Central - PubMed

Affiliation: Department of Statistics, University of California Los Angeles, Los Angeles, California, United States of America.

ABSTRACT
Many scientific investigations depend on obtaining data-driven, accurate, robust and computationally-tractable parameter estimates. In the face of unavoidable intrinsic variability, there are different algorithmic approaches, prior assumptions and fundamental principles for computing point and interval estimates. Efficient and reliable parameter estimation is critical in making inference about observable experiments, summarizing process characteristics and prediction of experimental behaviors. In this manuscript, we demonstrate simulation, construction, validation and interpretation of confidence intervals, under various assumptions, using the interactive web-based tools provided by the Statistics Online Computational Resource (http://www.SOCR.ucla.edu). Specifically, we present confidence interval examples for population means, with known or unknown population standard deviation; population variance; population proportion (exact and approximate), as well as confidence intervals based on bootstrapping or the asymptotic properties of the maximum likelihood estimates. Like all SOCR resources, these confidence interval resources may be openly accessed via an Internet-connected Java-enabled browser. The SOCR confidence interval applet enables the user to empirically explore and investigate the effects of the confidence-level, the sample-size and parameter of interest on the corresponding confidence interval. Two applications of the new interval estimation computational library are presented. The first one is a simulation of confidence interval estimating the US unemployment rate and the second application demonstrates the computations of point and interval estimates of hippocampal surface complexity for Alzheimers disease patients, mild cognitive impairment subjects and asymptomatic controls.

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Related in: MedlinePlus

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pone-0019178-g008: Input of the experiment when is not known.

Mentions: Confidence intervals for the mean with unknown standard deviation can be constructed analogously. These confidence intervals are based on the distribution and the length of different intervals will vary because the specific sample standard deviation is used in their construction. Consider the exponential distribution with parameter (mean of 0.2), sample size 60, confidence level 0.95, and number of intervals 50. Results of this experiment are shown on Figure 8 and Figure 9.


Confidence interval based parameter estimation--a new SOCR applet and activity.

Christou N, Dinov ID - PLoS ONE (2011)

Input of the experiment when  is not known.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3104980&req=5

pone-0019178-g008: Input of the experiment when is not known.
Mentions: Confidence intervals for the mean with unknown standard deviation can be constructed analogously. These confidence intervals are based on the distribution and the length of different intervals will vary because the specific sample standard deviation is used in their construction. Consider the exponential distribution with parameter (mean of 0.2), sample size 60, confidence level 0.95, and number of intervals 50. Results of this experiment are shown on Figure 8 and Figure 9.

Bottom Line: The SOCR confidence interval applet enables the user to empirically explore and investigate the effects of the confidence-level, the sample-size and parameter of interest on the corresponding confidence interval.Two applications of the new interval estimation computational library are presented.The first one is a simulation of confidence interval estimating the US unemployment rate and the second application demonstrates the computations of point and interval estimates of hippocampal surface complexity for Alzheimers disease patients, mild cognitive impairment subjects and asymptomatic controls.

View Article: PubMed Central - PubMed

Affiliation: Department of Statistics, University of California Los Angeles, Los Angeles, California, United States of America.

ABSTRACT
Many scientific investigations depend on obtaining data-driven, accurate, robust and computationally-tractable parameter estimates. In the face of unavoidable intrinsic variability, there are different algorithmic approaches, prior assumptions and fundamental principles for computing point and interval estimates. Efficient and reliable parameter estimation is critical in making inference about observable experiments, summarizing process characteristics and prediction of experimental behaviors. In this manuscript, we demonstrate simulation, construction, validation and interpretation of confidence intervals, under various assumptions, using the interactive web-based tools provided by the Statistics Online Computational Resource (http://www.SOCR.ucla.edu). Specifically, we present confidence interval examples for population means, with known or unknown population standard deviation; population variance; population proportion (exact and approximate), as well as confidence intervals based on bootstrapping or the asymptotic properties of the maximum likelihood estimates. Like all SOCR resources, these confidence interval resources may be openly accessed via an Internet-connected Java-enabled browser. The SOCR confidence interval applet enables the user to empirically explore and investigate the effects of the confidence-level, the sample-size and parameter of interest on the corresponding confidence interval. Two applications of the new interval estimation computational library are presented. The first one is a simulation of confidence interval estimating the US unemployment rate and the second application demonstrates the computations of point and interval estimates of hippocampal surface complexity for Alzheimers disease patients, mild cognitive impairment subjects and asymptomatic controls.

Show MeSH
Related in: MedlinePlus