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	<title>Neurobot &#187; Statistical Analysis</title>
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	<link>http://neurobot.bio.auth.gr</link>
	<description>A computational neuroscience and neuroinformatics blog</description>
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		<title>A non-parametric prototyping scheme for LFP dynamics and its application to detect changes in spontaneous UP-states due to cortical maturation and aging</title>
		<link>http://neurobot.bio.auth.gr/2014/a-non-parametric-prototyping-scheme-for-lfp-dynamics-and-its-application-to-detect-changes-in-spontaneous-up-states-due-to-cortical-maturation-and-aging/</link>
		<comments>http://neurobot.bio.auth.gr/2014/a-non-parametric-prototyping-scheme-for-lfp-dynamics-and-its-application-to-detect-changes-in-spontaneous-up-states-due-to-cortical-maturation-and-aging/#comments</comments>
		<pubDate>Thu, 26 Jun 2014 22:42:39 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[LFP]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[Statistical Analysis]]></category>
		<category><![CDATA[Trajectories]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3577</guid>
		<description><![CDATA[Spontaneous network activity in the form of Up and Down states plays an important role in the function of neural circuits and reflects intrinsic connectivity. Such cortical dynamics are shaped by genes, experience and intrinsic cellular properties and form the substrate upon which external stimuli and neuromodulation will impinge to determine cortical responses. The scope [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2014/a-non-parametric-prototyping-scheme-for-lfp-dynamics-and-its-application-to-detect-changes-in-spontaneous-up-states-due-to-cortical-maturation-and-aging/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Postdoctoral Research Position at Carnegie Mellon University</title>
		<link>http://neurobot.bio.auth.gr/2012/postdoctoral-research-position-at-carnegie-mellon-university/</link>
		<comments>http://neurobot.bio.auth.gr/2012/postdoctoral-research-position-at-carnegie-mellon-university/#comments</comments>
		<pubDate>Thu, 28 Jun 2012 15:59:45 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Jobs]]></category>
		<category><![CDATA[Brain Research]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[Neurophysiology]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3206</guid>
		<description><![CDATA[A postdoctoral research position is available at Carnegie Mellon University for collaborative research on statistical analysis of neural data. The research topics will be selected based, in part, on the skills and interests of the candidate. Work would be supervised by Rob Kass who is interested especially in developing new methods for analyzing data from [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2012/postdoctoral-research-position-at-carnegie-mellon-university/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>TRENTOOL: A Matlab open source toolbox to analyse information flow in time series data with transfer entropy</title>
		<link>http://neurobot.bio.auth.gr/2012/trentool-a-matlab-open-source-toolbox-to-analyse-information-flow-in-time-series-data-with-transfer-entropy/</link>
		<comments>http://neurobot.bio.auth.gr/2012/trentool-a-matlab-open-source-toolbox-to-analyse-information-flow-in-time-series-data-with-transfer-entropy/#comments</comments>
		<pubDate>Mon, 16 Apr 2012 10:42:39 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Software]]></category>
		<category><![CDATA[Neural Networks]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3176</guid>
		<description><![CDATA[TRENTOOL is an implementation of transfer entropy and mutual information analysis based on Wiener&#8217;s causality principle, aiming at the detection of model-free neuronal interactions in neural networks. TRENTOOL is available as an open-source MATLAB toolbox, available under an open source license (GPL v3), &#8220;that allows the user to handle the considerable complexity of this measure [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2012/trentool-a-matlab-open-source-toolbox-to-analyse-information-flow-in-time-series-data-with-transfer-entropy/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Book: &#8216;The Elements of  Statistical Learning&#8217;</title>
		<link>http://neurobot.bio.auth.gr/2012/book-the-elements-of-statistical-learning/</link>
		<comments>http://neurobot.bio.auth.gr/2012/book-the-elements-of-statistical-learning/#comments</comments>
		<pubDate>Fri, 09 Mar 2012 20:49:59 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Dimensionality Reduction]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3148</guid>
		<description><![CDATA[The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Download the book PDF (corrected 5th printing) here: http://www-stat.stanford.edu/~tibs/ElemStatLearn/]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2012/book-the-elements-of-statistical-learning/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Quality metrics to accompany spike sorting of extracellular signals</title>
		<link>http://neurobot.bio.auth.gr/2011/quality-metrics-to-accompany-spike-sorting-of-extracellular-signals/</link>
		<comments>http://neurobot.bio.auth.gr/2011/quality-metrics-to-accompany-spike-sorting-of-extracellular-signals/#comments</comments>
		<pubDate>Mon, 26 Dec 2011 10:46:17 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Brain Research]]></category>
		<category><![CDATA[Spike Sorting]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=3069</guid>
		<description><![CDATA[A review on visualization schemes and quality metrics used to evaluate the success of spike sorting procedures, published in Journal of Neuroscience. You may read the article here: Hill DN, Mehta SB and Kleinfeld D. Quality metrics to accompany spike sorting of extracellular signals. J Neurosci (2011) vol. 31 (24) pp. 8699-705]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2011/quality-metrics-to-accompany-spike-sorting-of-extracellular-signals/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>An Expectation-Maximization tutorial in neural signal analysis</title>
		<link>http://neurobot.bio.auth.gr/2011/an-expectation-maximization-tutorial-in-neural-signal-processing/</link>
		<comments>http://neurobot.bio.auth.gr/2011/an-expectation-maximization-tutorial-in-neural-signal-processing/#comments</comments>
		<pubDate>Mon, 03 Jan 2011 11:18:06 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Tutorials]]></category>
		<category><![CDATA[Clustering]]></category>
		<category><![CDATA[Spike Sorting]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2811</guid>
		<description><![CDATA[In this tutorial by Dr. Liam Paninski, the Expectation-Maximization (EM) algorithm is discussed and illustrated in a variety of neural examples. Key topics addressed: Example: Mixture models and spike sorting The method of bound optimization via auxiliary functions provides a useful alternative optimization technique The EM algorithm for maximizing the likelihood given hidden data may be derived [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2011/an-expectation-maximization-tutorial-in-neural-signal-processing/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Statistical Data Mining Tutorials</title>
		<link>http://neurobot.bio.auth.gr/2009/statistical-data-mining-tutorials/</link>
		<comments>http://neurobot.bio.auth.gr/2009/statistical-data-mining-tutorials/#comments</comments>
		<pubDate>Fri, 19 Jun 2009 08:47:11 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Tutorials]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2334</guid>
		<description><![CDATA[The following set of tutorials focus on many aspects of statistical data mining, including the foundations of probability, the foundations of statistical data analysis, and most of the classic machine learning and data mining algorithms. These include classification algorithms such as decision trees, neural nets, Bayesian classifiers, Support Vector Machines and cased-based (aka non-parametric) learning. [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2009/statistical-data-mining-tutorials/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>NeuroMAX Toolbox</title>
		<link>http://neurobot.bio.auth.gr/2008/neuromax-toolbox/</link>
		<comments>http://neurobot.bio.auth.gr/2008/neuromax-toolbox/#comments</comments>
		<pubDate>Fri, 03 Oct 2008 06:48:58 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Software]]></category>
		<category><![CDATA[Spike Sorting]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2238</guid>
		<description><![CDATA[NeuroMAX is a MATLAB-based software toolbox for the analysis of spike train data. NeuroMAX creates a chain of powerful analysis tools that meet your specific research goals. This tool chain, or Workspace, can be any combination of packaged NeuroMAX tools and your own custom MATLAB-based tools. NeuroMAX tools are grouped into four toolboxes: Spike Detection, [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2008/neuromax-toolbox/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Neural Ensemble Project</title>
		<link>http://neurobot.bio.auth.gr/2008/neural-ensemble-project/</link>
		<comments>http://neurobot.bio.auth.gr/2008/neural-ensemble-project/#comments</comments>
		<pubDate>Thu, 21 Aug 2008 07:30:28 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Software]]></category>
		<category><![CDATA[Neural Networks]]></category>
		<category><![CDATA[Neurophysiology]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2221</guid>
		<description><![CDATA[NeuralEnsemble is a multilateral effort to coordinate and organise Neuroscience software development efforts into a larger meta-simulator software system, a natural and alternate approach to incrementally address what is known as the complexity bottleneck, presently a major roadblock for neural modelling. NeuralEnsemble hosts Trac/Subversion servers for a number of open-source neuroscience tools: PyNN a Python [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2008/neural-ensemble-project/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>FIND toolbox &#8211; Finding Information in Neural Data</title>
		<link>http://neurobot.bio.auth.gr/2008/find-toolbox-finding-information-in-neural-data/</link>
		<comments>http://neurobot.bio.auth.gr/2008/find-toolbox-finding-information-in-neural-data/#comments</comments>
		<pubDate>Thu, 21 Aug 2008 07:17:44 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Software]]></category>
		<category><![CDATA[Clustering]]></category>
		<category><![CDATA[Spike Sorting]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2220</guid>
		<description><![CDATA[A Matlab-based, open-source analysis toolbox for multiple-neuron recordings and network simulations. Currently the FIND-Toolbox accommodates import of multiple proprietary data formats, based on the Neuroshare Project . Physiological data from different acquisition systems and Network simulations Environments can now be compared using identical analysis methods. This allows verifying of both results across experiments and laboratories [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2008/find-toolbox-finding-information-in-neural-data/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Review: Reliability, synchrony and noise</title>
		<link>http://neurobot.bio.auth.gr/2008/review-reliability-synchrony-and-noise/</link>
		<comments>http://neurobot.bio.auth.gr/2008/review-reliability-synchrony-and-noise/#comments</comments>
		<pubDate>Mon, 21 Jul 2008 08:28:52 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Brain Research]]></category>
		<category><![CDATA[Neurophysiology]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2214</guid>
		<description><![CDATA[This review describes a constructive role for noise in synchronizing populations of neurons. Trends Neurosci. 2008 Jul 4. [Epub ahead of print] Reliability, synchrony and noise. Ermentrout GB, Galán RF, Urban NN. The brain is noisy. Neurons receive tens of thousands of highly fluctuating inputs and generate spike trains that appear highly irregular. Much of [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2008/review-reliability-synchrony-and-noise/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>New datasharing website for computational neuroscience</title>
		<link>http://neurobot.bio.auth.gr/2008/new-datasharing-website-for-computational-neuroscience/</link>
		<comments>http://neurobot.bio.auth.gr/2008/new-datasharing-website-for-computational-neuroscience/#comments</comments>
		<pubDate>Fri, 04 Apr 2008 12:32:22 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Software]]></category>
		<category><![CDATA[Tutorials]]></category>
		<category><![CDATA[Neurophysiology]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2167</guid>
		<description><![CDATA[The new website http://www.crcns.org is available for sharing resources for computational neuroscience, such as high-quality experimental data sets, analytical tools and models. Currently, the website hosts resources whose preparation have been supported by a new funding track in the joint NSF/NIH program Collaborative Research in Computational Neuroscience. http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=5147 The resources currently available are electrophysiology data [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2008/new-datasharing-website-for-computational-neuroscience/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Chronux Analysis Software</title>
		<link>http://neurobot.bio.auth.gr/2008/chronux-analysis-software/</link>
		<comments>http://neurobot.bio.auth.gr/2008/chronux-analysis-software/#comments</comments>
		<pubDate>Fri, 07 Mar 2008 11:27:11 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Software]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=2156</guid>
		<description><![CDATA[Chronux is an open-source software package being developed for the analysis of neural data. It is a collaborative research effort based at the Mitra Lab in Cold Spring Harbor Laboratory that has grown out of the work of several groups. Chronux routines may be employed in the analysis of both point process and continuous data, [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2008/chronux-analysis-software/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Multiple neural spike train data analysis: state-of-the-art and future challenges</title>
		<link>http://neurobot.bio.auth.gr/2006/multiple-neural-spike-train-data-analysis-state-of-the-art-and-future-challenges/</link>
		<comments>http://neurobot.bio.auth.gr/2006/multiple-neural-spike-train-data-analysis-state-of-the-art-and-future-challenges/#comments</comments>
		<pubDate>Thu, 23 Feb 2006 00:17:38 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Documentation]]></category>
		<category><![CDATA[Spike Sorting]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=1999</guid>
		<description><![CDATA[Multiple electrodes are now a standard tool in neuroscience research that make it possible to study the simultaneous activity of several neurons in a given brain region or across different regions. The data from multi-electrode studies present important analysis challenges that must be resolved for optimal use of these neurophysiological measurements to answer questions about [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2006/multiple-neural-spike-train-data-analysis-state-of-the-art-and-future-challenges/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>A tutorial on Cross Correlation  &amp; Joint Peristimulus Time Histogram (JPSTH)</title>
		<link>http://neurobot.bio.auth.gr/2005/a-tutorial-on-cross-correlation-joint-peristimulus-time-histogram-jpsth/</link>
		<comments>http://neurobot.bio.auth.gr/2005/a-tutorial-on-cross-correlation-joint-peristimulus-time-histogram-jpsth/#comments</comments>
		<pubDate>Sat, 24 Sep 2005 17:29:18 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Tutorials]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=1995</guid>
		<description><![CDATA[This section provides an introduction to the analysis of data obtained from using small extracellular electrodes to record neural activity. There&#8217;s a great deal of interesting stuff to be learned from analyzing simultaneously recorded spike trains. Probably the most popular analysis involves the construction of the crosscorrelograms and JPSTHs. MULAB, University of Pennsylvania provides an [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2005/a-tutorial-on-cross-correlation-joint-peristimulus-time-histogram-jpsth/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Data Analysis Network</title>
		<link>http://neurobot.bio.auth.gr/2005/data-analysis-network/</link>
		<comments>http://neurobot.bio.auth.gr/2005/data-analysis-network/#comments</comments>
		<pubDate>Fri, 10 Jun 2005 12:54:28 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Software]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=1986</guid>
		<description><![CDATA[DAN is applied to gain better understanding of the neural foundation of information processing in the brain.The main idea of this project is to implement and to develop a new user-friendly software. A critical feature of brain theories is whether neurons convey a noisy rate code or a precise temporal code. One of most valuable [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2005/data-analysis-network/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>A Simple Matlab Data Analysis Tutorial</title>
		<link>http://neurobot.bio.auth.gr/2005/a-simple-matlab-data-analysis-tutorial/</link>
		<comments>http://neurobot.bio.auth.gr/2005/a-simple-matlab-data-analysis-tutorial/#comments</comments>
		<pubDate>Sun, 05 Jun 2005 12:01:27 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Tutorials]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=1981</guid>
		<description><![CDATA[A Matlab Data Analysis Tutorial for use on Computational Neuroscience methods. Assembled, edited and written by: Oren Shriki, oren.shriki@weizmann.ac.il Oren Farber, orenf@cc.huji.ac.il Dmitri Bibitchkov, dmitri.bibitchkov@weizmann.ac.il Access the Tutorial Here]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2005/a-simple-matlab-data-analysis-tutorial/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Advanced Statistics with MATLAB</title>
		<link>http://neurobot.bio.auth.gr/2005/advanced-statistics-with-matlab/</link>
		<comments>http://neurobot.bio.auth.gr/2005/advanced-statistics-with-matlab/#comments</comments>
		<pubDate>Sat, 04 Jun 2005 12:43:33 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Tutorials]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=1980</guid>
		<description><![CDATA[The purpose of this tutorial is to present several advanced statistics techniques using Matlab Statistics toolbox. Topics discussed in this tutorial include: 1. Covariance matrices and Eigenvalues 2. Principal component analysis 3. Canonical Correlation 4. Polynomial fit for a set of points Access this Tutorial Here By Daniela Raicu draicu@cs.depaul.edu School of Computer Science, Telecommunications, [...]]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2005/advanced-statistics-with-matlab/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Statistics with MATLAB</title>
		<link>http://neurobot.bio.auth.gr/2005/statistics-with-matlab/</link>
		<comments>http://neurobot.bio.auth.gr/2005/statistics-with-matlab/#comments</comments>
		<pubDate>Fri, 03 Jun 2005 12:39:15 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Tutorials]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=1979</guid>
		<description><![CDATA[The purpose of this tutorial is to present several statistics techniques using Matlab Statistics toolbox. Topics discussed in this tutorial include: 1. Descriptive statistics 2. Linear Models 3. Cluster analysis 4. Principal component analysis Access this Tutorial Here By Daniela Raicu draicu@cs.depaul.edu School of Computer Science, Telecommunications, and Information Systems DePaul University, Chicago, IL 60604]]></description>
		<wfw:commentRss>http://neurobot.bio.auth.gr/2005/statistics-with-matlab/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Introduction to Probability Theory and Statistics</title>
		<link>http://neurobot.bio.auth.gr/2005/introduction-to-probability-theory-and-statistics/</link>
		<comments>http://neurobot.bio.auth.gr/2005/introduction-to-probability-theory-and-statistics/#comments</comments>
		<pubDate>Tue, 22 Feb 2005 09:17:32 +0000</pubDate>
		<dc:creator>Dimitrios A. Adamos</dc:creator>
				<category><![CDATA[Tutorials]]></category>
		<category><![CDATA[Statistical Analysis]]></category>

		<guid isPermaLink="false">http://neurobot.bio.auth.gr/?p=1970</guid>
		<description><![CDATA[Introduction to Probability Theory and Statistic by Javier R. Movellan. Read the full document Copyright 1996,1998, 2002 Javier R. Movellan. This is an open source document. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free [...]]]></description>
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		<slash:comments>0</slash:comments>
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