Decisions based on data yield superior results than those made on hunches. Manufacturing processes are no exception to this axiom. Statistical data analytics plays a major role in manufacturing. Process and product quality are majorly driven by the efficacy of associated data and scientific methods of analysis and inferencing. This text discusses scientific data methods used in process development, process qualification, measurement qualification, and screening of incoming material for desired quality. The topics here cover design of experiments. Efficient ways of experimentation lead to process insights and enable control over quality in an efficient way. Design and analysis of factorial experiments are discussed here. Process once developed needs to be qualified for its suitability to perform in a sustained manner. Methods of process capability and stability evaluation are discussed. An outline of how process management is implemented through statistical methods is given. Various tests and studies that go into robust and usefully accurate measurement of analytes are enumerated. Acceptance sampling is an important aspect of regulating the quality of incoming material with sampling. Acceptance sampling terminologies and their applications are discussed here.