- published: 05 Mar 2015
- views: 1278
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This video was created as part of a job interview process - I'm setting it free.
The slides are here: http://garthtarr.com/pres/RobIntro
Note that you may need to refresh the slides to get the network graphs to appear.
References:
Location: Hodges-Lehmann estimator
http://en.wikipedia.org/wiki/Hodges-Lehmann_estimator
Hodges, Lehmann (1963). Estimation of location based on ranks. Annals of Mathematical Statistics 34(2): 598-611. DOI: http://dx.doi.org/10.1214/aoms/1177704172
Covariance: Minimum Covariance Determinant (MCD) estimator
Hubert, Debruyne (2010). Minimum covariance determinant. Wiley Interdisciplinary Reviews: Computational Statistics, 2: 36-43. DOI: http://dx.doi.org/10.1002/wics.61
Sparse precision matrix estimation: Graphical lasso
Friedman, Hastie, Tibshirani (2008). Sparse inverse covariance estimation with the graphical lasso. Biostatistics, 9(3): 432-441. DOI: http://dx.doi.org/10.1093/biostatistics/kxm045
Robust precision matrix estimation
Tarr, Müller, Weber (2015). Robust estimation of precision matrices under cellwise contamination. Computational Statistics & Data Analysis, to appear. DOI: http://dx.doi.org/10.1016/j.csda.2015.02.005
Robust scale estimation
Tarr, Müller, Weber (2012). A robust scale estimator based on pairwise means. Journal of Nonparametric Statistics, 24(1): 187-199. DOI: http://dx.doi.org/10.1080/10485252.2011.621424
Overview of robust estimation of scale and dependence
Tarr, (2014). Quantile Based Estimation of Scale and Dependence. PhD Thesis. University of Sydney, Australia. http://hdl.handle.net/2123/10590
Robust statistics
Robust statistics are statistics with good performance for data drawn from a wide range of probability distributions, especially for distributions that are not normal.Robust statistical methods have been developed for many common problems, such as estimating location, scale and regression parameters.
=======Image-Copyright-Info=======
Image is in public domain
Author-Info: en:User:Tolstoy the Cat
Image Source: https://en.wikipedia.org/wiki/File:SpeedOfLight.png
=======Image-Copyright-Info========
-Video is targeted to blind users
Attribution:
Article text available under CC-BY-SA
image source in video
https://www.youtube.com/watch?v=fcRaulHFJYI
- published: 29 Jan 2016
- views: 22
An example of robust statistics using R. For more on statistics visit http://www.wekaleamstudios.co.uk and browse.
- published: 20 Dec 2011
- views: 2402
Robust statistics from USA failed to back USD
https://www.instaforex.com
- published: 17 Oct 2014
- views: 205
3D Slicer is a free open source software distributed under a BSD-style license (http://www.slicer.org).
In this video you can watch:
1) Segmentation of lateral ventricles by Threshold Effect;
2) Segmentation of brain using the module “Robust Statistics Segmenter”.
References
Fedorov A, Beichel R, Kalpathy-Cramer J, Finet J, Fillion-Robin J-C, Pujol S, Bauer C, Jennings D, Fennessy F, Sonka M, Buatti J, Aylward SR, Miller JV, Pieper S, Kikinis R. 3D Slicer as an Image Computing Platform for the Quantitative Imaging Network. Magnetic Resonance Imaging. 2012 Nov;30(9):1323-41. PMID: 22770690.
Gao Y, Kikinis R, Bouix S, Shenton M, Tannenbaum A. A 3D interactive multi-object segmentation tool using local robust statistics driven active contours. Med Image Anal. 2012 Aug;16(6):1216-27. doi: 10.1016/j.media.2012.06.002. Epub 2012 Jul 6.
- published: 30 Dec 2015
- views: 333
Brief user's Guide for my Excel Template aimed to perform some "traditional" and "robust" statistic. Just enter the observations of your sample, and with few mouse's click you can get your Trimmed sample, Winsorized sample, Random sample, as well as some descriptive statistics. You can enter the needed Trimming fraction, Confidence level for the range of population mean, the size of the Random sample drawn from your original sample. Box-plots and Frequency distribution Histograms help you to describe your data. The spreadsheet can handle two samples entered by user, and can perform a t-Test (both with traditional and robust estimators) to verify the difference between the samples' means.
Info:
http://xoomer.virgilio.it/gianmarco.alberti/index_file/Page395.htm
http://www.academia.edu/1300783/XLTRS-Excel_Template_for_Robust_Statistics
- published: 20 May 2009
- views: 4822
Robust statistics provides an alternative approach to standard statistical methods, such as those for estimating location, scale and regression parameters. The motivation is to produce estimators that are not unduly affected by small departures from the model assumptions under which these standard methods are usually derived: the standard methods are comparatively badly affected.
Robust statistics seeks to provide methods that emulate popular statistical methods, but which are not unduly affected by outliers or other small departures from model assumptions. In statistics, classical estimation methods rely heavily on assumptions which are often not met in practice. In particular, it is often assumed that the data errors are normally distributed, at least approximately, or that the central limit theorem can be relied on to produce normally distributed estimates. Unfortunately, when there are outliers in the data, classical estimators often have very poor performance, when judged using the breakdown point and the influence function, described below.
This page contains text from Wikipedia, the Free Encyclopedia -
http://en.wikipedia.org/wiki/Robust_statistics
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
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11:02A brief introduction to robust statistics
A brief introduction to robust statisticsA brief introduction to robust statistics
This video was created as part of a job interview process - I'm setting it free. The slides are here: http://garthtarr.com/pres/RobIntro Note that you may need to refresh the slides to get the network graphs to appear. References: Location: Hodges-Lehmann estimator http://en.wikipedia.org/wiki/Hodges-Lehmann_estimator Hodges, Lehmann (1963). Estimation of location based on ranks. Annals of Mathematical Statistics 34(2): 598-611. DOI: http://dx.doi.org/10.1214/aoms/1177704172 Covariance: Minimum Covariance Determinant (MCD) estimator Hubert, Debruyne (2010). Minimum covariance determinant. Wiley Interdisciplinary Reviews: Computational Statistics, 2: 36-43. DOI: http://dx.doi.org/10.1002/wics.61 Sparse precision matrix estimation: Graphical lasso Friedman, Hastie, Tibshirani (2008). Sparse inverse covariance estimation with the graphical lasso. Biostatistics, 9(3): 432-441. DOI: http://dx.doi.org/10.1093/biostatistics/kxm045 Robust precision matrix estimation Tarr, Müller, Weber (2015). Robust estimation of precision matrices under cellwise contamination. Computational Statistics & Data Analysis, to appear. DOI: http://dx.doi.org/10.1016/j.csda.2015.02.005 Robust scale estimation Tarr, Müller, Weber (2012). A robust scale estimator based on pairwise means. Journal of Nonparametric Statistics, 24(1): 187-199. DOI: http://dx.doi.org/10.1080/10485252.2011.621424 Overview of robust estimation of scale and dependence Tarr, (2014). Quantile Based Estimation of Scale and Dependence. PhD Thesis. University of Sydney, Australia. http://hdl.handle.net/2123/10590 -
1:26Robust statistics
Robust statisticsRobust statistics
-
20:47Robust statistics
Robust statisticsRobust statistics
Robust statistics Robust statistics are statistics with good performance for data drawn from a wide range of probability distributions, especially for distributions that are not normal.Robust statistical methods have been developed for many common problems, such as estimating location, scale and regression parameters. =======Image-Copyright-Info======= Image is in public domain Author-Info: en:User:Tolstoy the Cat Image Source: https://en.wikipedia.org/wiki/File:SpeedOfLight.png =======Image-Copyright-Info======== -Video is targeted to blind users Attribution: Article text available under CC-BY-SA image source in video https://www.youtube.com/watch?v=fcRaulHFJYI -
21:17B08 - Robust Statistics
B08 - Robust StatisticsB08 - Robust Statistics
-
3:28Basic Robust Statistics
Basic Robust StatisticsBasic Robust Statistics
An example of robust statistics using R. For more on statistics visit http://www.wekaleamstudios.co.uk and browse. -
1:46Robust statistics from USA failed to back USD
Robust statistics from USA failed to back USDRobust statistics from USA failed to back USD
Robust statistics from USA failed to back USD https://www.instaforex.com -
7:303. Statistics for One Variable - 6 Examining robust statistics for univariate analyses
3. Statistics for One Variable - 6 Examining robust statistics for univariate analyses3. Statistics for One Variable - 6 Examining robust statistics for univariate analyses
-
7:303D Slicer: Threshold Effect and Robust Statistics Segmenter
3D Slicer: Threshold Effect and Robust Statistics Segmenter3D Slicer: Threshold Effect and Robust Statistics Segmenter
3D Slicer is a free open source software distributed under a BSD-style license (http://www.slicer.org). In this video you can watch: 1) Segmentation of lateral ventricles by Threshold Effect; 2) Segmentation of brain using the module “Robust Statistics Segmenter”. References Fedorov A, Beichel R, Kalpathy-Cramer J, Finet J, Fillion-Robin J-C, Pujol S, Bauer C, Jennings D, Fennessy F, Sonka M, Buatti J, Aylward SR, Miller JV, Pieper S, Kikinis R. 3D Slicer as an Image Computing Platform for the Quantitative Imaging Network. Magnetic Resonance Imaging. 2012 Nov;30(9):1323-41. PMID: 22770690. Gao Y, Kikinis R, Bouix S, Shenton M, Tannenbaum A. A 3D interactive multi-object segmentation tool using local robust statistics driven active contours. Med Image Anal. 2012 Aug;16(6):1216-27. doi: 10.1016/j.media.2012.06.002. Epub 2012 Jul 6. -
3:59Excel Template for Robust Statistics (see Video for download location)
Excel Template for Robust Statistics (see Video for download location)Excel Template for Robust Statistics (see Video for download location)
Brief user's Guide for my Excel Template aimed to perform some "traditional" and "robust" statistic. Just enter the observations of your sample, and with few mouse's click you can get your Trimmed sample, Winsorized sample, Random sample, as well as some descriptive statistics. You can enter the needed Trimming fraction, Confidence level for the range of population mean, the size of the Random sample drawn from your original sample. Box-plots and Frequency distribution Histograms help you to describe your data. The spreadsheet can handle two samples entered by user, and can perform a t-Test (both with traditional and robust estimators) to verify the difference between the samples' means. Info: http://xoomer.virgilio.it/gianmarco.alberti/index_file/Page395.htm http://www.academia.edu/1300783/XLTRS-Excel_Template_for_Robust_Statistics -
8:407. Statistics for Associations - 8 Computing robust statistics for bivariate associations
7. Statistics for Associations - 8 Computing robust statistics for bivariate associations7. Statistics for Associations - 8 Computing robust statistics for bivariate associations
- Arithmetic mean
- Bayesian method
- Bias (statistics)
- Breakdown point
- Brian D. Ripley
- Central tendency
- Classic data sets
- Decision theory
- Estimator
- Expected value
- Fisher consistency
- Gâteaux derivative
- Huber loss function
- Iid
- Impulse response
- Influence function
- Interquartile range
- Kalman filter
- L-estimator
- Lipschitz constant
- Location parameter
- M-estimator
- M-estimators
- Mathematical Reviews
- Median
- Minimax
- Minimax regret
- Mixture density
- Mixture model
- One-sided limit
- Outliers
- Ozone hole
- Parameter space
- Peter J. Rousseeuw
- Peter. J. Huber
- Pivotal quantity
- Possibility theory
- Prior distribution
- R. Douglas Martin
- Range (statistics)
- Resistant statistics
- Robust regression
- Robust statistics
- Scale parameter
- Scenario analysis
- Smoothed bootstrap
- Standard deviation
- Statistics
- Stress testing
- T-distribution
- Test statistic
- Trimmed estimator
- Trimmed mean
- Utility function
- Winsorising
- Winsorizing
- WP references
- WP Verifiability
-
A brief introduction to robust statistics
This video was created as part of a job interview process - I'm setting it free. The slides are here: http://garthtarr.com/pres/RobIntro Note that you may need to refresh the slides to get the network graphs to appear. References: Location: Hodges-Lehmann estimator http://en.wikipedia.org/wiki/Hodges-Lehmann_estimator Hodges, Lehmann (1963). Estimation of location based on ranks. Annals of Mathematical Statistics 34(2): 598-611. DOI: http://dx.doi.org/10.1214/aoms/1177704172 Covariance: Minimum Covariance Determinant (MCD) estimator Hubert, Debruyne (2010). Minimum covariance determinant. Wiley Interdisciplinary Reviews: Computational Statistics, 2: 36-43. DOI: http://dx.doi.org/10.1002/wics.61 Sparse precision matrix estimation: Graphical lasso Friedman, Hastie, Tibshirani (2008). S... -
Robust statistics
-
Robust statistics
Robust statistics Robust statistics are statistics with good performance for data drawn from a wide range of probability distributions, especially for distributions that are not normal.Robust statistical methods have been developed for many common problems, such as estimating location, scale and regression parameters. =======Image-Copyright-Info======= Image is in public domain Author-Info: en:User:Tolstoy the Cat Image Source: https://en.wikipedia.org/wiki/File:SpeedOfLight.png =======Image-Copyright-Info======== -Video is targeted to blind users Attribution: Article text available under CC-BY-SA image source in video https://www.youtube.com/watch?v=fcRaulHFJYI -
B08 - Robust Statistics
-
Basic Robust Statistics
An example of robust statistics using R. For more on statistics visit http://www.wekaleamstudios.co.uk and browse. -
Robust statistics from USA failed to back USD
Robust statistics from USA failed to back USD https://www.instaforex.com -
3. Statistics for One Variable - 6 Examining robust statistics for univariate analyses
-
3D Slicer: Threshold Effect and Robust Statistics Segmenter
3D Slicer is a free open source software distributed under a BSD-style license (http://www.slicer.org). In this video you can watch: 1) Segmentation of lateral ventricles by Threshold Effect; 2) Segmentation of brain using the module “Robust Statistics Segmenter”. References Fedorov A, Beichel R, Kalpathy-Cramer J, Finet J, Fillion-Robin J-C, Pujol S, Bauer C, Jennings D, Fennessy F, Sonka M, Buatti J, Aylward SR, Miller JV, Pieper S, Kikinis R. 3D Slicer as an Image Computing Platform for the Quantitative Imaging Network. Magnetic Resonance Imaging. 2012 Nov;30(9):1323-41. PMID: 22770690. Gao Y, Kikinis R, Bouix S, Shenton M, Tannenbaum A. A 3D interactive multi-object segmentation tool using local robust statistics driven active contours. Med Image Anal. 2012 Aug;16(6):1216-27. doi: 10.... -
Excel Template for Robust Statistics (see Video for download location)
Brief user's Guide for my Excel Template aimed to perform some "traditional" and "robust" statistic. Just enter the observations of your sample, and with few mouse's click you can get your Trimmed sample, Winsorized sample, Random sample, as well as some descriptive statistics. You can enter the needed Trimming fraction, Confidence level for the range of population mean, the size of the Random sample drawn from your original sample. Box-plots and Frequency distribution Histograms help you to describe your data. The spreadsheet can handle two samples entered by user, and can perform a t-Test (both with traditional and robust estimators) to verify the difference between the samples' means. Info: http://xoomer.virgilio.it/gianmarco.alberti/index_file/Page395.htm http://www.academia.edu/130... -
7. Statistics for Associations - 8 Computing robust statistics for bivariate associations
A brief introduction to robust statistics
- Order: Reorder
- Duration: 11:02
- Updated: 05 Mar 2015
- views: 1278
This video was created as part of a job interview process - I'm setting it free.
The slides are here: http://garthtarr.com/pres/RobIntro
Note that you may nee...
This video was created as part of a job interview process - I'm setting it free.
The slides are here: http://garthtarr.com/pres/RobIntro
Note that you may need to refresh the slides to get the network graphs to appear.
References:
Location: Hodges-Lehmann estimator
http://en.wikipedia.org/wiki/Hodges-Lehmann_estimator
Hodges, Lehmann (1963). Estimation of location based on ranks. Annals of Mathematical Statistics 34(2): 598-611. DOI: http://dx.doi.org/10.1214/aoms/1177704172
Covariance: Minimum Covariance Determinant (MCD) estimator
Hubert, Debruyne (2010). Minimum covariance determinant. Wiley Interdisciplinary Reviews: Computational Statistics, 2: 36-43. DOI: http://dx.doi.org/10.1002/wics.61
Sparse precision matrix estimation: Graphical lasso
Friedman, Hastie, Tibshirani (2008). Sparse inverse covariance estimation with the graphical lasso. Biostatistics, 9(3): 432-441. DOI: http://dx.doi.org/10.1093/biostatistics/kxm045
Robust precision matrix estimation
Tarr, Müller, Weber (2015). Robust estimation of precision matrices under cellwise contamination. Computational Statistics & Data Analysis, to appear. DOI: http://dx.doi.org/10.1016/j.csda.2015.02.005
Robust scale estimation
Tarr, Müller, Weber (2012). A robust scale estimator based on pairwise means. Journal of Nonparametric Statistics, 24(1): 187-199. DOI: http://dx.doi.org/10.1080/10485252.2011.621424
Overview of robust estimation of scale and dependence
Tarr, (2014). Quantile Based Estimation of Scale and Dependence. PhD Thesis. University of Sydney, Australia. http://hdl.handle.net/2123/10590
wn.com/A Brief Introduction To Robust Statistics
This video was created as part of a job interview process - I'm setting it free.
The slides are here: http://garthtarr.com/pres/RobIntro
Note that you may need to refresh the slides to get the network graphs to appear.
References:
Location: Hodges-Lehmann estimator
http://en.wikipedia.org/wiki/Hodges-Lehmann_estimator
Hodges, Lehmann (1963). Estimation of location based on ranks. Annals of Mathematical Statistics 34(2): 598-611. DOI: http://dx.doi.org/10.1214/aoms/1177704172
Covariance: Minimum Covariance Determinant (MCD) estimator
Hubert, Debruyne (2010). Minimum covariance determinant. Wiley Interdisciplinary Reviews: Computational Statistics, 2: 36-43. DOI: http://dx.doi.org/10.1002/wics.61
Sparse precision matrix estimation: Graphical lasso
Friedman, Hastie, Tibshirani (2008). Sparse inverse covariance estimation with the graphical lasso. Biostatistics, 9(3): 432-441. DOI: http://dx.doi.org/10.1093/biostatistics/kxm045
Robust precision matrix estimation
Tarr, Müller, Weber (2015). Robust estimation of precision matrices under cellwise contamination. Computational Statistics & Data Analysis, to appear. DOI: http://dx.doi.org/10.1016/j.csda.2015.02.005
Robust scale estimation
Tarr, Müller, Weber (2012). A robust scale estimator based on pairwise means. Journal of Nonparametric Statistics, 24(1): 187-199. DOI: http://dx.doi.org/10.1080/10485252.2011.621424
Overview of robust estimation of scale and dependence
Tarr, (2014). Quantile Based Estimation of Scale and Dependence. PhD Thesis. University of Sydney, Australia. http://hdl.handle.net/2123/10590
- published: 05 Mar 2015
- views: 1278
Robust statistics
- Order: Reorder
- Duration: 1:26
- Updated: 01 Oct 2014
- views: 990
- published: 01 Oct 2014
- views: 990
Robust statistics
- Order: Reorder
- Duration: 20:47
- Updated: 29 Jan 2016
- views: 22
Robust statistics
Robust statistics are statistics with good performance for data drawn from a wide range of probability distributions, especially for distri...
Robust statistics
Robust statistics are statistics with good performance for data drawn from a wide range of probability distributions, especially for distributions that are not normal.Robust statistical methods have been developed for many common problems, such as estimating location, scale and regression parameters.
=======Image-Copyright-Info=======
Image is in public domain
Author-Info: en:User:Tolstoy the Cat
Image Source: https://en.wikipedia.org/wiki/File:SpeedOfLight.png
=======Image-Copyright-Info========
-Video is targeted to blind users
Attribution:
Article text available under CC-BY-SA
image source in video
https://www.youtube.com/watch?v=fcRaulHFJYI
wn.com/Robust Statistics
Robust statistics
Robust statistics are statistics with good performance for data drawn from a wide range of probability distributions, especially for distributions that are not normal.Robust statistical methods have been developed for many common problems, such as estimating location, scale and regression parameters.
=======Image-Copyright-Info=======
Image is in public domain
Author-Info: en:User:Tolstoy the Cat
Image Source: https://en.wikipedia.org/wiki/File:SpeedOfLight.png
=======Image-Copyright-Info========
-Video is targeted to blind users
Attribution:
Article text available under CC-BY-SA
image source in video
https://www.youtube.com/watch?v=fcRaulHFJYI
- published: 29 Jan 2016
- views: 22
B08 - Robust Statistics
- Order: Reorder
- Duration: 21:17
- Updated: 31 Jan 2015
- views: 565
- published: 31 Jan 2015
- views: 565
Basic Robust Statistics
- Order: Reorder
- Duration: 3:28
- Updated: 20 Dec 2011
- views: 2402
An example of robust statistics using R. For more on statistics visit http://www.wekaleamstudios.co.uk and browse.
An example of robust statistics using R. For more on statistics visit http://www.wekaleamstudios.co.uk and browse.
wn.com/Basic Robust Statistics
An example of robust statistics using R. For more on statistics visit http://www.wekaleamstudios.co.uk and browse.
- published: 20 Dec 2011
- views: 2402
Robust statistics from USA failed to back USD
- Order: Reorder
- Duration: 1:46
- Updated: 17 Oct 2014
- views: 205
Robust statistics from USA failed to back USD
https://www.instaforex.com
- published: 17 Oct 2014
- views: 205
3. Statistics for One Variable - 6 Examining robust statistics for univariate analyses
- Order: Reorder
- Duration: 7:30
- Updated: 11 Feb 2014
- views: 678
- published: 11 Feb 2014
- views: 678
3D Slicer: Threshold Effect and Robust Statistics Segmenter
- Order: Reorder
- Duration: 7:30
- Updated: 30 Dec 2015
- views: 333
3D Slicer is a free open source software distributed under a BSD-style license (http://www.slicer.org).
In this video you can watch:
1) Segmentation of lateral ...
3D Slicer is a free open source software distributed under a BSD-style license (http://www.slicer.org).
In this video you can watch:
1) Segmentation of lateral ventricles by Threshold Effect;
2) Segmentation of brain using the module “Robust Statistics Segmenter”.
References
Fedorov A, Beichel R, Kalpathy-Cramer J, Finet J, Fillion-Robin J-C, Pujol S, Bauer C, Jennings D, Fennessy F, Sonka M, Buatti J, Aylward SR, Miller JV, Pieper S, Kikinis R. 3D Slicer as an Image Computing Platform for the Quantitative Imaging Network. Magnetic Resonance Imaging. 2012 Nov;30(9):1323-41. PMID: 22770690.
Gao Y, Kikinis R, Bouix S, Shenton M, Tannenbaum A. A 3D interactive multi-object segmentation tool using local robust statistics driven active contours. Med Image Anal. 2012 Aug;16(6):1216-27. doi: 10.1016/j.media.2012.06.002. Epub 2012 Jul 6.
wn.com/3D Slicer Threshold Effect And Robust Statistics Segmenter
3D Slicer is a free open source software distributed under a BSD-style license (http://www.slicer.org).
In this video you can watch:
1) Segmentation of lateral ventricles by Threshold Effect;
2) Segmentation of brain using the module “Robust Statistics Segmenter”.
References
Fedorov A, Beichel R, Kalpathy-Cramer J, Finet J, Fillion-Robin J-C, Pujol S, Bauer C, Jennings D, Fennessy F, Sonka M, Buatti J, Aylward SR, Miller JV, Pieper S, Kikinis R. 3D Slicer as an Image Computing Platform for the Quantitative Imaging Network. Magnetic Resonance Imaging. 2012 Nov;30(9):1323-41. PMID: 22770690.
Gao Y, Kikinis R, Bouix S, Shenton M, Tannenbaum A. A 3D interactive multi-object segmentation tool using local robust statistics driven active contours. Med Image Anal. 2012 Aug;16(6):1216-27. doi: 10.1016/j.media.2012.06.002. Epub 2012 Jul 6.
- published: 30 Dec 2015
- views: 333
Excel Template for Robust Statistics (see Video for download location)
- Order: Reorder
- Duration: 3:59
- Updated: 20 May 2009
- views: 4822
Brief user's Guide for my Excel Template aimed to perform some "traditional" and "robust" statistic. Just enter the observations of your sample, and with few mo...
Brief user's Guide for my Excel Template aimed to perform some "traditional" and "robust" statistic. Just enter the observations of your sample, and with few mouse's click you can get your Trimmed sample, Winsorized sample, Random sample, as well as some descriptive statistics. You can enter the needed Trimming fraction, Confidence level for the range of population mean, the size of the Random sample drawn from your original sample. Box-plots and Frequency distribution Histograms help you to describe your data. The spreadsheet can handle two samples entered by user, and can perform a t-Test (both with traditional and robust estimators) to verify the difference between the samples' means.
Info:
http://xoomer.virgilio.it/gianmarco.alberti/index_file/Page395.htm
http://www.academia.edu/1300783/XLTRS-Excel_Template_for_Robust_Statistics
wn.com/Excel Template For Robust Statistics (See Video For Download Location)
Brief user's Guide for my Excel Template aimed to perform some "traditional" and "robust" statistic. Just enter the observations of your sample, and with few mouse's click you can get your Trimmed sample, Winsorized sample, Random sample, as well as some descriptive statistics. You can enter the needed Trimming fraction, Confidence level for the range of population mean, the size of the Random sample drawn from your original sample. Box-plots and Frequency distribution Histograms help you to describe your data. The spreadsheet can handle two samples entered by user, and can perform a t-Test (both with traditional and robust estimators) to verify the difference between the samples' means.
Info:
http://xoomer.virgilio.it/gianmarco.alberti/index_file/Page395.htm
http://www.academia.edu/1300783/XLTRS-Excel_Template_for_Robust_Statistics
- published: 20 May 2009
- views: 4822
7. Statistics for Associations - 8 Computing robust statistics for bivariate associations
- Order: Reorder
- Duration: 8:40
- Updated: 11 Feb 2014
- views: 349
- published: 11 Feb 2014
- views: 349
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11:02
A brief introduction to robust statistics
This video was created as part of a job interview process - I'm setting it free.
The slid...
published: 05 Mar 2015
A brief introduction to robust statistics
A brief introduction to robust statistics
- Report rights infringement
- published: 05 Mar 2015
- views: 1278
1:26
Robust statistics
published: 01 Oct 2014
Robust statistics
Robust statistics
- Report rights infringement
- published: 01 Oct 2014
- views: 990
20:47
Robust statistics
Robust statistics
Robust statistics are statistics with good performance for data drawn...
published: 29 Jan 2016
Robust statistics
Robust statistics
- Report rights infringement
- published: 29 Jan 2016
- views: 22
21:17
B08 - Robust Statistics
published: 31 Jan 2015
B08 - Robust Statistics
B08 - Robust Statistics
- Report rights infringement
- published: 31 Jan 2015
- views: 565
3:28
Basic Robust Statistics
An example of robust statistics using R. For more on statistics visit http://www.wekaleams...
published: 20 Dec 2011
Basic Robust Statistics
Basic Robust Statistics
- Report rights infringement
- published: 20 Dec 2011
- views: 2402
1:46
Robust statistics from USA failed to back USD
Robust statistics from USA failed to back USD
https://www.instaforex.com
published: 17 Oct 2014
Robust statistics from USA failed to back USD
Robust statistics from USA failed to back USD
- Report rights infringement
- published: 17 Oct 2014
- views: 205
7:30
3. Statistics for One Variable - 6 Examining robust statistics for univariate analyses
published: 11 Feb 2014
3. Statistics for One Variable - 6 Examining robust statistics for univariate analyses
3. Statistics for One Variable - 6 Examining robust statistics for univariate analyses
- Report rights infringement
- published: 11 Feb 2014
- views: 678
7:30
3D Slicer: Threshold Effect and Robust Statistics Segmenter
3D Slicer is a free open source software distributed under a BSD-style license (http://www...
published: 30 Dec 2015
3D Slicer: Threshold Effect and Robust Statistics Segmenter
3D Slicer: Threshold Effect and Robust Statistics Segmenter
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- published: 30 Dec 2015
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Excel Template for Robust Statistics (see Video for download location)
Brief user's Guide for my Excel Template aimed to perform some "traditional" and "robust" ...
published: 20 May 2009
Excel Template for Robust Statistics (see Video for download location)
Excel Template for Robust Statistics (see Video for download location)
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- published: 20 May 2009
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7. Statistics for Associations - 8 Computing robust statistics for bivariate associations
published: 11 Feb 2014
7. Statistics for Associations - 8 Computing robust statistics for bivariate associations
7. Statistics for Associations - 8 Computing robust statistics for bivariate associations
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- published: 11 Feb 2014
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A brief introduction to robust statistics...
Robust statistics...
Robust statistics...
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Robust statistics from USA failed to back USD...
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3D Slicer: Threshold Effect and Robust Statistics ...
Excel Template for Robust Statistics (see Video fo...
