Statistical Significnace of a Survey Analysis We understand that the bigger the sample size, the more reliable is the result of the data analysis of a survey. How do you determine with confidence that a survey results are valid and representative of the population?
We can create boxplots to check for outliers or histograms to see if the sample is normal. What other preliminary statistical checks are necessary?


How do you determine with confidence that a survey results are valid and representative of the population?

Well, you see, you can't just check this is the case.  Let me explain.
A very pervasive problem in surveys is known as non-response bias.  People unfortunately do not like to respond to surveys, and those who do respond are all alike in some way (my guess is that they are all older, white, middle class citizens but I could be wrong). No statistical procedure -- in the absence of any information towards the existence of this bias -- is capable of detecting it.  This bias threatens the validity of the survey.
Even if you were to ask for things like Socioeconomic status, race, age, etc., there could always be one more variable you forgot to account for which threatens the validity through this bias.  That being said, if you're willing to make assumptions about which variables effect this non-response, you could attempt post-stratification.
