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        <title><![CDATA[Jez : Weblog items tagged with statistics]]></title>
        <description><![CDATA[The weblog for Jez, hosted on Holyrood Park.]]></description>
        <link>http://elearningblogs.education.ed.ac.uk/oldelgg/elgg/jezbate/weblog/</link>        
        <item>
            <title><![CDATA[Grappling with stats]]></title>
            <link>http://elearningblogs.education.ed.ac.uk/oldelgg/elgg/jezbate/weblog/1973.html</link>
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            <pubDate>Wed, 11 Mar 2009 00:13:32 GMT</pubDate>
		<dc:subject><![CDATA[blood types]]></dc:subject>
		<dc:subject><![CDATA[statistics]]></dc:subject>
		<dc:subject><![CDATA[quantitative]]></dc:subject>
            <description><![CDATA[<p>Good to see from other blogs that I am not alone in struggling with the stats. Reassuring. I have found my reacquaintance with maths and hateful numbers quite demotivating, though, however clear the rationale for its study. As usual, there is no quiet retreat for the part-time student to get to grips with these things; work, family and temptation must be contended with by a systematic and determined effort. </p><p>I posted a comment to Christine that I&nbsp;think that once a definite need to use such a quantitative&nbsp;approach materialises in a piece of research, it will seem less abstract. The task on the course is important but (necessarily) still quite arbitrary. If, just for example, I wanted to measure the participation in various types of online course of people of the 4 different blood types (!!), then I might be able to use SPSS to describe various relationships.</p><p>One question is: what kind of merit would such a study have? There are so many variables.</p>]]></description>
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