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