Optimization & A/B Testing Statistics
Optimization & A/B Testing Statistics
Speed up your a/b tests by doing it right from the start.
Students will gain an understanding of what instant and rapid inductions are, how they work, and how to execute them safely.
Description
Whether you've got a lean startup or a fat Fortune 500, the faster you learn the faster you'll grow. Optimization and a/b testing is at the heart of learning fast.
I guarantee you will learn something in this course that will raise your skill level. With the 30-day money-back guarantee, you can't lose.
We start with the basics, then cover the 8 steps of running a solid a/b test. Next we dive deep into the statistics behind hypothesis testing. In the long-run you will save your organization headaches by setting up tests correctly and analyzing them with the right statistical rigour.
There is double and triple digit ROI around optimization for companies that figure it out. Start now and impress your colleagues on Monday morning.
Topics include:
Examples of a/b tests
Hypothesis testing
Measurement as risk reduction
Selecting a KPI or success metric
8 Steps for Running an A/B Test
Selecting from amongs a/b test and MVT test designs
Lift Threshold
Null Hypothesis
Statistical significance
Sample size estimates
confidence interval
test statistic
t-tests
standard error of the mean
chi-square
Fischer Exact test
Statistical Power
Type I error
Type II error
p-values
How to choose what statistical test to run
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