I am just starting a self learning beginner course on statistics (majored in applied math but had no background on stats). Here is one naive question I encountered when trying to understand point estimation.
Confusion for point estimates of a certain model arises when one obtains different parameter estimates for different sample sizes. Suppose an example: if one is to find the incidence of lung cancer in mice and want do develop a model for it, and in one experiment, the researchers were to take 100 mice as the sample size, in which 10 of the mice has cancer, and assuming a Binomial Distribution, the estimate parameter can be $p = 10/100 = 0.1$, what if another sample was taken, say the sample size is now 80, in which 20 mice has cancer, and our new estimate is $p = 20/80 = 0.25$ - which is quite different from our previous estimates. In this case, we can get many different estimates for our model's true parameter, which one should we choose? Or am I asking a question that will be answered in my later chapters (of my self study materials)?