Yes and no. Ultimately it's almost never true that the null hypothesis is true. If you think about it there will almost always be some sort of difference in means/variance/whatever_you're_looking_at between the groups. So if you increase the sample size you increase the power to detect that difference. So yes, with a large enough sample you will most likely reject the null. Now that doesn't mean the difference is practically significant though. Also, if by some chance the null hypothesis really is true then by increasing sample size you keep the same type 1 error rate.
No, it could get a little smaller, it could get a little bigger. (There's more to it than this but oh well...) But the effect size isn't magically going to get larger just because you take a larger sample size. That doesn't make sense. The result might become more significant (smaller p-value) because you have a better estimate of the error and the standard error of the difference will decrease with a larger sample size. But that doesn't mean the estimate effect itself will get larger.2. If a study shows that Group A mean is 5% greater than Group B, does it mean if i have bigger sample size Group A mean will only get bigger? Or it can also go in the reverse direction (where Group B mean gets bigger)?
Ultimately with a larger sample size you're getting a better estimate of what the true means actually are.





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