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	<title>Comments on: Seasonal Adjustment &#8211; Preliminary Approaches</title>
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		<title>By: DSA Insights &#187; Blog Archive &#187; Seasonality in Data</title>
		<link>http://peltiertech.com/WordPress/seasonal-adjustment-preliminary-approaches/comment-page-1/#comment-6514</link>
		<dc:creator>DSA Insights &#187; Blog Archive &#187; Seasonality in Data</dc:creator>
		<pubDate>Thu, 04 Dec 2008 12:28:17 +0000</pubDate>
		<guid isPermaLink="false">http://peltiertech.com/WordPress/?p=105#comment-6514</guid>
		<description>[...] Jon Peltier - Blog post about seasonality [...]</description>
		<content:encoded><![CDATA[<p>[...] Jon Peltier &#8211; Blog post about seasonality [...]</p>
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		<title>By: Jon Peltier</title>
		<link>http://peltiertech.com/WordPress/seasonal-adjustment-preliminary-approaches/comment-page-1/#comment-1260</link>
		<dc:creator>Jon Peltier</dc:creator>
		<pubDate>Wed, 04 Jun 2008 19:38:46 +0000</pubDate>
		<guid isPermaLink="false">http://peltiertech.com/WordPress/?p=105#comment-1260</guid>
		<description>Len -

When I return to this, I will have a mechanism for deciding whether some points are outliers and should be excluded. Special causes (switching hosts) can be excluded, maybe so can a couple other days if they are beyond the confidence intervals computed for the rough fits of the cycle plot.</description>
		<content:encoded><![CDATA[<p>Len -</p>
<p>When I return to this, I will have a mechanism for deciding whether some points are outliers and should be excluded. Special causes (switching hosts) can be excluded, maybe so can a couple other days if they are beyond the confidence intervals computed for the rough fits of the cycle plot.</p>
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		<title>By: len</title>
		<link>http://peltiertech.com/WordPress/seasonal-adjustment-preliminary-approaches/comment-page-1/#comment-1256</link>
		<dc:creator>len</dc:creator>
		<pubDate>Wed, 04 Jun 2008 18:55:39 +0000</pubDate>
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		<description>Maybe it would be useful to drop local outliers, in your case probably by distance from the trend line in orthogonal view (third chart).  There is no reason for May 8th and the likes to be included in this analysis..</description>
		<content:encoded><![CDATA[<p>Maybe it would be useful to drop local outliers, in your case probably by distance from the trend line in orthogonal view (third chart).  There is no reason for May 8th and the likes to be included in this analysis..</p>
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		<title>By: Jon Peltier</title>
		<link>http://peltiertech.com/WordPress/seasonal-adjustment-preliminary-approaches/comment-page-1/#comment-1221</link>
		<dc:creator>Jon Peltier</dc:creator>
		<pubDate>Tue, 03 Jun 2008 15:09:50 +0000</pubDate>
		<guid isPermaLink="false">http://peltiertech.com/WordPress/?p=105#comment-1221</guid>
		<description>Derek - Thanks for reminding me to look in my library. I own a few books on data analysis in Excel (not Mike&#039;s, though I respect what work he&#039;s shared on his web site and in the Excel community). My next step, after the unguided (misguided?) analysis above, should be to review the approaches presented in these books, and in the links from the Census Bureau and other authorities. Then hopefully a bit wiser, try again.</description>
		<content:encoded><![CDATA[<p>Derek &#8211; Thanks for reminding me to look in my library. I own a few books on data analysis in Excel (not Mike&#8217;s, though I respect what work he&#8217;s shared on his web site and in the Excel community). My next step, after the unguided (misguided?) analysis above, should be to review the approaches presented in these books, and in the links from the Census Bureau and other authorities. Then hopefully a bit wiser, try again.</p>
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		<title>By: derek</title>
		<link>http://peltiertech.com/WordPress/seasonal-adjustment-preliminary-approaches/comment-page-1/#comment-1220</link>
		<dc:creator>derek</dc:creator>
		<pubDate>Tue, 03 Jun 2008 14:43:00 +0000</pubDate>
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		<description>Michael Middleton&#039;s &lt;a href=&quot;http://www.amazon.com/Data-Analysis-Using-Microsoft-Excel/dp/0534402933&quot; rel=&quot;nofollow&quot;&gt;&lt;i&gt;Data Analysis Using Microsoft Excel&lt;/i&gt;&lt;/a&gt; also contains a chapter with several good methods of time series forecasting. Naturally they do the opposite of seasonally adjust, but you can get the same effect by removing the seasonal component of the forecast.</description>
		<content:encoded><![CDATA[<p>Michael Middleton&#8217;s <a href="http://www.amazon.com/Data-Analysis-Using-Microsoft-Excel/dp/0534402933" rel="nofollow"><i>Data Analysis Using Microsoft Excel</i></a> also contains a chapter with several good methods of time series forecasting. Naturally they do the opposite of seasonally adjust, but you can get the same effect by removing the seasonal component of the forecast.</p>
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