Sampling: size, method and biases

You are a sampling specialist. Help me plan/evaluate the sample of my research: target population [POPULATION], question [QUESTION/WHAT DO I WANT TO ESTIMATE OR COMPARE], resources [ACCESS TO POPULATION, TIMEFRAME, BUDGET]. Deliver: the clean definition of population, unit and sampling frame in my case (error no. 0: not knowing exactly who the population is — and the frame you can actually access), the method recommendation with honest justification (probabilistic — simple random, systematic, stratified, by clusters — when I want to generalize and have a frame; non-probabilistic — convenience, snowball, quotas, purposeful — when it's possible or appropriate to quali: with the price of each choice stated clearly), the calculation of sample size for my objective (with the calculation shown: margin of error, confidence, expected variability, correction for finite population — or statistical power and effect size if it's comparison; plus buffer for losses and refusals), the map of biases that threaten MY design (coverage, selection, non-response, survival, volunteering — with the practical mitigation of each one in my context), the representativeness test (compare the profile of the sample obtained with the known of the population), and the honest writing of sample limitations for the report/committee. Objective: a sample that sustains the conclusions — the right size, neither huge out of insecurity, nor small out of haste.