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Power is the ability of a test to correctly identify a significant effect. Suppose we are performing a test to see if the mean age of two groups is different or not. If the power of this test is 0.8, we can see there is a 80% chance that if the two groups have different mean age, the test is going to correctly detect it

Probability of type 1 error is the probability of rejecting a null hypothesis when it is true. when we filter out all the values below the mean, the distribution becomes more skewed and the results become more significant, resulting in an increase in the type 1 error

Sample size is based on a few factors - type 1 error rate threshold, type 2 error rate threshold and effect size. Based on these factors, I will compute the sample size that is needed to detect the effect from the experiment. I will check if all the experiment parameters are satisfied, the sample ratio is along expected lines and all the guardrail metrics are as expected. Then, I'll conduct a statistical test to see if the change is statistically significant. I will also evaluate if the change is practically significant for the costs incurred to implement this. Also, I will check if the effect size is seen across user groups or is restricted to specific set of users.

I have been working on same project since last 3 years, I want to explore different projects and learn new skills and Technologies with current market trends