ABSTRACT
Estimation theory is a branch of statistics and signal processing that deals with estimating the values of parameters based on measured/empirical data that has a random component. Estimation theory can be found at the heart of many electronic signal processing systems designed to extract information; these systems include radar, sonar, speech, image, communications, control and seismology. This chapter presents some of the principles involved with sampling and estimation theories. It describes the standard error of the means and estimates the mean and standard deviation of a population from sample data. The concepts of elementary sampling theory and estimation theories provide the basis for a more detailed study of inspection, control and quality control techniques used in industry. Usually when the word sample is used, it means that a random sample is taken. If each member of a population has the same chance of being selected, then a sample taken from that population is called random.
