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	<title>itfeature.com</title>
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	<description>An Introduction and Tutorial site for Statistics.</description>
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		<title>Difference between Common Log and Natural Log</title>
		<link>http://itfeature.com/difference-between-common-log-and-natural-log/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=difference-between-common-log-and-natural-log</link>
		<comments>http://itfeature.com/difference-between-common-log-and-natural-log/#comments</comments>
		<pubDate>Thu, 10 May 2012 02:15:46 +0000</pubDate>
		<dc:creator></dc:creator>
				<category><![CDATA[Miscellaneous Articles]]></category>
		<category><![CDATA[Common Log]]></category>
		<category><![CDATA[Exponential Functions]]></category>
		<category><![CDATA[Growth Functions]]></category>
		<category><![CDATA[Log]]></category>
		<category><![CDATA[Natural Log]]></category>

		<guid isPermaLink="false">http://itfeature.com/?p=207</guid>
		<description><![CDATA[Difference between Common Log and Natural Log The Logarithm of a number is the exponent by which another fixed value the base has to be raised to produce that number. For example the logarithm of 1000 to base 10 is 3as 1000=103. Logarithms were introduced by John Napier in the early 17th century for simplification <a href='http://itfeature.com/difference-between-common-log-and-natural-log/' class='excerpt-more'>[...]</a>]]></description>
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		<title>Cumulative Frequency Distribution and Polygon</title>
		<link>http://itfeature.com/cumulative-frequency-distribution-and-polygon/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=cumulative-frequency-distribution-and-polygon</link>
		<comments>http://itfeature.com/cumulative-frequency-distribution-and-polygon/#comments</comments>
		<pubDate>Mon, 07 May 2012 16:59:44 +0000</pubDate>
		<dc:creator></dc:creator>
				<category><![CDATA[Chart and Graphics]]></category>
		<category><![CDATA[Charts and Graphics]]></category>
		<category><![CDATA[Cumulative Frequency Distribution]]></category>
		<category><![CDATA[Ogive]]></category>
		<category><![CDATA[Polygon]]></category>

		<guid isPermaLink="false">http://itfeature.com/?p=192</guid>
		<description><![CDATA[Cumulative Frequency Distribution and Polygon A cumulative frequency distribution (cumulative frequency curve or ogive) and a cumulative frequency polygon require cumulative frequencies. The cumulative frequency is denoted by CF and for a class interval it is obtained by adding the frequency of all the preceding classes including that class. It indicates the total number of <a href='http://itfeature.com/cumulative-frequency-distribution-and-polygon/' class='excerpt-more'>[...]</a>]]></description>
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		<title>Inverse Regression Analysis</title>
		<link>http://itfeature.com/inverse-regression-analysis/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=inverse-regression-analysis</link>
		<comments>http://itfeature.com/inverse-regression-analysis/#comments</comments>
		<pubDate>Fri, 04 May 2012 03:30:53 +0000</pubDate>
		<dc:creator></dc:creator>
				<category><![CDATA[Correlation and Regression Analysis]]></category>
		<category><![CDATA[Inverse Regression Analysis]]></category>
		<category><![CDATA[Simple Regression Analysis]]></category>
		<category><![CDATA[Inverse Regression]]></category>
		<category><![CDATA[Regression analysis]]></category>

		<guid isPermaLink="false">http://itfeature.com/?p=179</guid>
		<description><![CDATA[Inverse Regression Analysis In most regression problems we have to determine the value of corresponding to a given value of . We will consider the inverse problem, which is called inverse regression or calibration. Assume we have known values of and their corresponding values, which both form a simple linear regression model and we have <a href='http://itfeature.com/inverse-regression-analysis/' class='excerpt-more'>[...]</a>]]></description>
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		<title>Binomial Probability Distribution is a discrete probability distribution describing</title>
		<link>http://itfeature.com/binomial-probability-distribution-is-a-discrete-probability-distribution-describing/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=binomial-probability-distribution-is-a-discrete-probability-distribution-describing</link>
		<comments>http://itfeature.com/binomial-probability-distribution-is-a-discrete-probability-distribution-describing/#comments</comments>
		<pubDate>Tue, 01 May 2012 18:55:25 +0000</pubDate>
		<dc:creator></dc:creator>
				<category><![CDATA[Binomial Probability Distribution]]></category>
		<category><![CDATA[Discrete Probability Distribution]]></category>
		<category><![CDATA[Probability]]></category>
		<category><![CDATA[Bernoulli Trials]]></category>
		<category><![CDATA[Probability Distribution]]></category>

		<guid isPermaLink="false">http://itfeature.com/?p=170</guid>
		<description><![CDATA[Binomial Probability Distributions Bernoulli Trials Many experiments consists of repeated independent trials and each trial have only two possible outcomes such as head or tail, right or wrong, alive or dead, defective or non-defective etc. If the probability of each outcome remains the same (constant) throughout the trials, then such trials are called the Bernoulli <a href='http://itfeature.com/binomial-probability-distribution-is-a-discrete-probability-distribution-describing/' class='excerpt-more'>[...]</a>]]></description>
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		<title>Coefficient of Determination</title>
		<link>http://itfeature.com/coefficient-of-determination/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=coefficient-of-determination</link>
		<comments>http://itfeature.com/coefficient-of-determination/#comments</comments>
		<pubDate>Sat, 28 Apr 2012 20:02:57 +0000</pubDate>
		<dc:creator></dc:creator>
				<category><![CDATA[Model Selection Criteria]]></category>
		<category><![CDATA[Coefficient of Determination]]></category>
		<category><![CDATA[Goodness of fit test]]></category>

		<guid isPermaLink="false">http://itfeature.com/?p=154</guid>
		<description><![CDATA[Coefficient of Determination is a useful statistics to check the value of regression fit. measures the proportion of total variation about the mean explained by the regression. Ris the correlation between and and is usually the multiple correlation coefficient. can take values as high as when all the  values are different. When repeats runs exists <a href='http://itfeature.com/coefficient-of-determination/' class='excerpt-more'>[...]</a>]]></description>
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		<item>
		<title>Pseudo Randomness Process</title>
		<link>http://itfeature.com/pseudo-randomness-process/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=pseudo-randomness-process</link>
		<comments>http://itfeature.com/pseudo-randomness-process/#comments</comments>
		<pubDate>Sat, 28 Apr 2012 10:39:24 +0000</pubDate>
		<dc:creator></dc:creator>
				<category><![CDATA[Statistical Simulation]]></category>
		<category><![CDATA[Pseudo Random Number]]></category>
		<category><![CDATA[Pseudo Random Process]]></category>

		<guid isPermaLink="false">http://itfeature.com/?p=150</guid>
		<description><![CDATA[Statistical Simulation A pseudorandom process is a process that appears to be random but actually it is not. Pseudorandom sequences typically exhibit statistical randomness while being generated by an entirely deterministic causal process. Such a process is easier to produce than a genuinely random one, and has the benefit that it can be used again <a href='http://itfeature.com/pseudo-randomness-process/' class='excerpt-more'>[...]</a>]]></description>
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		<title>Linear Congruential Generator (LCG)</title>
		<link>http://itfeature.com/linear-congruential-generator-lcg/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=linear-congruential-generator-lcg</link>
		<comments>http://itfeature.com/linear-congruential-generator-lcg/#comments</comments>
		<pubDate>Tue, 17 Apr 2012 19:09:52 +0000</pubDate>
		<dc:creator></dc:creator>
				<category><![CDATA[Statistical Simulation]]></category>
		<category><![CDATA[Lehmer Random Number Generator]]></category>
		<category><![CDATA[Linear Contruential Generator]]></category>
		<category><![CDATA[Simulation]]></category>

		<guid isPermaLink="false">http://itfeature.com/?p=141</guid>
		<description><![CDATA[Statistical Simulation The building block of a simulation study is the ability to generate random numbers where a random number represents the value of a random variable uniformly distributed on (0,1). The generator is defined by the recurrence relation: and are given positive integers, is either and quantity is pseudo number. Some conditions are: m&#62;0;  <a href='http://itfeature.com/linear-congruential-generator-lcg/' class='excerpt-more'>[...]</a>]]></description>
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		<title>Simulation is used before an existing system is altered or a new system built,</title>
		<link>http://itfeature.com/simulation-is-used-before-an-existing-system-is-altered-or-a-new-system-built/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=simulation-is-used-before-an-existing-system-is-altered-or-a-new-system-built</link>
		<comments>http://itfeature.com/simulation-is-used-before-an-existing-system-is-altered-or-a-new-system-built/#comments</comments>
		<pubDate>Sat, 07 Apr 2012 17:12:43 +0000</pubDate>
		<dc:creator></dc:creator>
				<category><![CDATA[Statistical Simulation]]></category>
		<category><![CDATA[Simulation]]></category>

		<guid isPermaLink="false">http://itfeature.com/?p=135</guid>
		<description><![CDATA[Statistical Simulation Simulation is used before an existing system is altered or a new system built, to reduce the chances of failure to meet specifications, to eliminate unforeseen bottlenecks, to prevent under or over-utilization of resources and to optimize system performance. Models are simulated versions/results. Simulation depends on unknown (or external/ impositions/ factors) parameters and <a href='http://itfeature.com/simulation-is-used-before-an-existing-system-is-altered-or-a-new-system-built/' class='excerpt-more'>[...]</a>]]></description>
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		<title>MATLAB stands for &#8220;Matrix Laboratory&#8221; and is an interactive</title>
		<link>http://itfeature.com/matlab-stands-for-matrix-laboratory-and-is-an-interactive/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=matlab-stands-for-matrix-laboratory-and-is-an-interactive</link>
		<comments>http://itfeature.com/matlab-stands-for-matrix-laboratory-and-is-an-interactive/#comments</comments>
		<pubDate>Sat, 07 Apr 2012 16:57:33 +0000</pubDate>
		<dc:creator></dc:creator>
				<category><![CDATA[Introduction to Matlab]]></category>
		<category><![CDATA[Matlab]]></category>
		<category><![CDATA[Matlab Introduction]]></category>

		<guid isPermaLink="false">http://itfeature.com/?p=132</guid>
		<description><![CDATA[Introduction to Matlab MATLAB stands for &#8220;Matrix Laboratory&#8221; and is an interactive, matrix-based system and fourth-generation programming language from the Mathworks Inc., is mathematics software. Matlab helps to perform statistical analysis and gives the user complete freedom to implement specific algorithms and perform complex custom-tailored operations. Matlab has a command-driven approach. Commands with appropriate arguments <a href='http://itfeature.com/matlab-stands-for-matrix-laboratory-and-is-an-interactive/' class='excerpt-more'>[...]</a>]]></description>
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		<title>What is a measure of central tendency &#8230;.</title>
		<link>http://itfeature.com/what-is-a-measure-of-central-tendency/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=what-is-a-measure-of-central-tendency</link>
		<comments>http://itfeature.com/what-is-a-measure-of-central-tendency/#comments</comments>
		<pubDate>Thu, 05 Apr 2012 15:40:22 +0000</pubDate>
		<dc:creator></dc:creator>
				<category><![CDATA[Basic Statistics]]></category>
		<category><![CDATA[Central Tendency]]></category>
		<category><![CDATA[mean]]></category>
		<category><![CDATA[median]]></category>
		<category><![CDATA[mode]]></category>
		<category><![CDATA[Quantiative Variable]]></category>

		<guid isPermaLink="false">http://itfeature.com/?p=130</guid>
		<description><![CDATA[Basic Statistics What is a measure of central tendency and what are the common measures of central tendency? Also when is the median preferred over the mean? A measure of central tendency is the single numerical value considered most typical of the values of a quantitative variable. The most common measures of central tendency are <a href='http://itfeature.com/what-is-a-measure-of-central-tendency/' class='excerpt-more'>[...]</a>]]></description>
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