Date: Fri, 15 May 2015 05:08:03 +0000
<p style="margin: 0px 0px 10px; color: #224422; font-family: sans-serif; font-size: 14px; line-height: 24px;"> This week's episode dicusses z-scores, also known as standard score. This score describes the distance (in standard deviations) that an observation is away from the mean of the population. A closely related top is the <a href="http://en.wikipedia.org/wiki/68%E2%80%9395%E2%80%9399.7_rule" style="color: #337ab7; text-decoration: none; background-color: transparent;">68-95-99.7 rule</a> which tells us that (approximately) 68% of a normally distributed population lies within one standard deviation of the mean, 95 within 2, and 99.7 within 3.</p> <p style="margin: 0px 0px 10px; color: #224422; font-family: sans-serif; font-size: 14px; line-height: 24px;"> Kyle and Linh Da discuss z-scores in the context of human height. If you'd like to calculate your own z-score for height, you can do so below. They further discuss how a z-score can also describe the likelihood that some statistical result is due to chance. Thus, if the significance of a finding can be said to be <span class="MathJax" id="MathJax-Element-1-Frame" style="display: inline; line-height: normal; white-space: nowrap; float: none; direction: ltr; border: 0px; padding: 0px; margin: 0px;"><span class="math" id="MathJax-Span-1"><span><span><span class="mrow" id="MathJax-Span-2"><span class="mn" id="MathJax-Span-3">3</span><span class="mi" id="MathJax-Span-4">σ</span></span></span></span></span></span>, that means that it's 99.7% likely not due to chance, or only 0.3% likely to be due to chance.</p>
