This chapter deals with some aspects of two sources of systematic error in surveys: non-response and measurement error. The quality of the obtained response is discussed first with a focus on non-response bias estimation and non-response bias reduction. Measurement error is studied by evaluating the quality of registered responses through question wording, order, and response scale effects. The different approaches to measurement error are discussed. Practical examples of dealing with bias and measurement error are offered. These include the evaluation of non-(response) rates and response enhancement strategies, comparing cooperative and reluctant respondents on non-response issues based on the analysis of European Social Survey. Concerning measurement error, the split ballot approach and multitrait multimethod are extensively discussed including theoretical concepts and methods/models, and an example of acquiescence when a balanced set of items is available. The chapter also presents some debates concerning theoretical construct and model developments in the respective fields, and emphasizes that both errors are strongly related. This means response distributions, correlations, and regression parameters can be seriously affected.