WTF? This was a somewhat incoherent list of "stats stuff"; I especially liked the equation:<p><pre><code> signal
confidence = ------ x \sqrt(sample size)
noise
</code></pre>
(none of the terms in the 'equation' were defined beforehand) which was led into by 'so when someone says “is your result statistically significant?” then it means he is really asking “What is the likely hood that your result has not occurred by chance”' No no no no no no no no no no non.<p>Edit: corrected despair-induced typos.
In real world the statistics is usually the most useful part of math. Analysing data without some basic statistics lead often to erroneous conclusions.<p>What surprise me, that it doesn't get attention it deserves at pre-university education. A lot of lessons in math are about geometry, algebra, etc. which are a great way to learn logical and abstract thinking, but aren't as useful as statistics.
<i>Q1. When your website conversion rate jumps from 10% to 12% then is it 2% rise in conversion rate or 20% rise in conversion rate?</i><p>This question doesn't have a clear answer, because the values are already percentages. Imagine the original numbers refer to apples. First there were 10 apples, then 12 apples. The absolute increase is 2 apples; the relative increase is 20%. Obviously, if you say "the increase is __ apples" or "the increase is __ %" there's only one right way to replace the blanks with numbers. But since 10 and 12 are already percentages, the absolute and relative changes would be stated as "the increase is 2%" (absolute increase) and "the increase is 20%" (relative increase.) They mean different things, but they're both correct statements if interpreted correctly.<p>In practice, people will expect one and interpret the other as wrong. Knowing which one they expect is not a matter of statistics.
Shameless plug: <a href="https://bitdeli.com" rel="nofollow">https://bitdeli.com</a> lets you put theory into practice - you can build your own web analytics in plain and simple Python.<p>Feel free to ping me if you need help getting started (or a longer trial :)
If you want to have a go rolling your own web analytics calculations, I would recommend setting up SnowPlow (<a href="https://github.com/snowplow/snowplow" rel="nofollow">https://github.com/snowplow/snowplow</a>) and then following through the SnowPlow Web Analyst's Cookbook (start with the simple recipes here: <a href="http://snowplowanalytics.com/analytics/basic-recipes.html" rel="nofollow">http://snowplowanalytics.com/analytics/basic-recipes.html</a>).<p>Here's a simple example for unique visitors by month:<p><pre><code> SELECT
YEAR(dt),
MONTH(dt),
COUNT(DISTINCT(user_id))
FROM events
GROUP BY YEAR(dt), MONTH(dt) ;</code></pre>
Nice article. It could have done with a better example for %difference. %difference is used when neither value is more important or topical than the other.