Summary of my knowledge about statistics or hypothesis test in particular

Reason for summary
I feel it's time to stop looking into more statistics or hypothesis test in particular. Anyway I'm not going to work as a statistician. I should position myself as marketing analyst with solid knowledge of statistics and capable of conducting complicated hypothesis test for marketing test.

List of my knowledge about hypothesis test

• parametric testing
• one sample test (z test and t test)
• two sample test (mean test and standard deviation test)
• one way ANOVA
• two way ANOVA (full factorial design and fractal factorial design - Taguchi method)
• non parametric testing (normal distribution test)

The next question is what is the value to marketing. Maybe it is easy to explain it in design of experiment. hypothesis test is one step of design of experiment

Marketing campaign can be considered as one type of experiment with input as marketing mix (4P, price, place, promotion, and product), output as goals (revenue, profit, market share and etc) and market itself as black box. After you have insight about the market, you might find a few key factors. You will try to find the optimal combination to maximize your goal with minimum cost. That's where hypothesis test comes in and help it.

Application,
One interesting application might be in Google ads optimization. Here is an very interesting youtube video to find the best ads with different heading, first description line, second description line and url. One thing to note is that, in practice, people care about the optimal level of the factor, rather than know the factor really has impact on the experiment.

P.S. From tomorrow, I need to focus more on marketing strategy and cases instead of techniques in statistics. Don't be a nerd.