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	<title>
	Comments on: Comprehensive Guide to Statistics in A/B Testing	</title>
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		<title>
		By: Silver Ringvee		</title>
		<link>https://www.reflectivedata.com/comprehensive-guide-to-statistics-in-a-b-testing/#comment-29116</link>

		<dc:creator><![CDATA[Silver Ringvee]]></dc:creator>
		<pubDate>Tue, 23 Feb 2021 09:54:16 +0000</pubDate>
		<guid isPermaLink="false">http://reflectivedata.com/?p=2877#comment-29116</guid>

					<description><![CDATA[In reply to &lt;a href=&quot;https://www.reflectivedata.com/comprehensive-guide-to-statistics-in-a-b-testing/#comment-29114&quot;&gt;Soorya Prakash&lt;/a&gt;.

Hey Soorya,

Thank you for the comment.

This calculator should be a good starting point: https://www.convert.com/calculator/revenue-per-visitor/

To dig deeper, I&#039;d recommend you look at the Mann-Whitney-Wilcoxon rank-sum test in Python or R.

Silver]]></description>
			<content:encoded><![CDATA[<p>In reply to <a href="https://www.reflectivedata.com/comprehensive-guide-to-statistics-in-a-b-testing/#comment-29114">Soorya Prakash</a>.</p>
<p>Hey Soorya,</p>
<p>Thank you for the comment.</p>
<p>This calculator should be a good starting point: <a href="https://www.convert.com/calculator/revenue-per-visitor/" rel="nofollow ugc">https://www.convert.com/calculator/revenue-per-visitor/</a></p>
<p>To dig deeper, I&#8217;d recommend you look at the Mann-Whitney-Wilcoxon rank-sum test in Python or R.</p>
<p>Silver</p>
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		<title>
		By: Soorya Prakash		</title>
		<link>https://www.reflectivedata.com/comprehensive-guide-to-statistics-in-a-b-testing/#comment-29114</link>

		<dc:creator><![CDATA[Soorya Prakash]]></dc:creator>
		<pubDate>Tue, 23 Feb 2021 00:39:45 +0000</pubDate>
		<guid isPermaLink="false">http://reflectivedata.com/?p=2877#comment-29114</guid>

					<description><![CDATA[A truly helpful article :)

In our team, we are working on calculating confidence intervals for a non-binomial metric like Average Revenue Per User. Would you happen to know a good calculator for this? Or any literature that throws some light on this?]]></description>
			<content:encoded><![CDATA[<p>A truly helpful article 🙂</p>
<p>In our team, we are working on calculating confidence intervals for a non-binomial metric like Average Revenue Per User. Would you happen to know a good calculator for this? Or any literature that throws some light on this?</p>
]]></content:encoded>
		
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		<item>
		<title>
		By: Leasting Fallvo		</title>
		<link>https://www.reflectivedata.com/comprehensive-guide-to-statistics-in-a-b-testing/#comment-22434</link>

		<dc:creator><![CDATA[Leasting Fallvo]]></dc:creator>
		<pubDate>Tue, 17 Mar 2020 23:40:20 +0000</pubDate>
		<guid isPermaLink="false">http://reflectivedata.com/?p=2877#comment-22434</guid>

					<description><![CDATA[I feel like a &quot;comprehensive guide&quot; would include at least one formula for sample size]]></description>
			<content:encoded><![CDATA[<p>I feel like a &#8220;comprehensive guide&#8221; would include at least one formula for sample size</p>
]]></content:encoded>
		
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		<item>
		<title>
		By: Silver Ringvee		</title>
		<link>https://www.reflectivedata.com/comprehensive-guide-to-statistics-in-a-b-testing/#comment-21531</link>

		<dc:creator><![CDATA[Silver Ringvee]]></dc:creator>
		<pubDate>Tue, 26 Nov 2019 09:30:40 +0000</pubDate>
		<guid isPermaLink="false">http://reflectivedata.com/?p=2877#comment-21531</guid>

					<description><![CDATA[In reply to &lt;a href=&quot;https://www.reflectivedata.com/comprehensive-guide-to-statistics-in-a-b-testing/#comment-21527&quot;&gt;Sarah&lt;/a&gt;.

I recommend this one from CXL https://conversionxl.com/ab-test-calculator/]]></description>
			<content:encoded><![CDATA[<p>In reply to <a href="https://www.reflectivedata.com/comprehensive-guide-to-statistics-in-a-b-testing/#comment-21527">Sarah</a>.</p>
<p>I recommend this one from CXL <a href="https://conversionxl.com/ab-test-calculator/" rel="nofollow ugc">https://conversionxl.com/ab-test-calculator/</a></p>
]]></content:encoded>
		
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		<item>
		<title>
		By: Sarah		</title>
		<link>https://www.reflectivedata.com/comprehensive-guide-to-statistics-in-a-b-testing/#comment-21527</link>

		<dc:creator><![CDATA[Sarah]]></dc:creator>
		<pubDate>Tue, 26 Nov 2019 09:25:56 +0000</pubDate>
		<guid isPermaLink="false">http://reflectivedata.com/?p=2877#comment-21527</guid>

					<description><![CDATA[Can you recommend a good calculator for A/B testing statistics?]]></description>
			<content:encoded><![CDATA[<p>Can you recommend a good calculator for A/B testing statistics?</p>
]]></content:encoded>
		
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		<title>
		By: How Analytics Can Help Improve Team Productivity &#38; Performance - Reflective Data		</title>
		<link>https://www.reflectivedata.com/comprehensive-guide-to-statistics-in-a-b-testing/#comment-20022</link>

		<dc:creator><![CDATA[How Analytics Can Help Improve Team Productivity &#38; Performance - Reflective Data]]></dc:creator>
		<pubDate>Thu, 18 Jul 2019 11:31:40 +0000</pubDate>
		<guid isPermaLink="false">http://reflectivedata.com/?p=2877#comment-20022</guid>

					<description><![CDATA[[&#8230;] response, you can try some classic A/B testing when it comes to team composition and organization (provided you know how to interpret the results). Make some alterations, let people work for a few weeks, then compare the analytics of that period [&#8230;]]]></description>
			<content:encoded><![CDATA[<p>[&#8230;] response, you can try some classic A/B testing when it comes to team composition and organization (provided you know how to interpret the results). Make some alterations, let people work for a few weeks, then compare the analytics of that period [&#8230;]</p>
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