ABSTRACT
The sampling and estimation theories are most reliable when the population is approximately normal and the sample is selected randomly. Estimation is the simplest form of inferential statistics, which uses known sample evidence to draw conclusions regarding unknown population characteristics. Estimation can be discussed in two groups, point and interval. The absolute value of the difference between the value of the sample mean and the value of the population mean is called the sampling error. The size of the sample depends on the distribution of the characteristics in the population; therefore, the population must be clearly defined. This chapter now combines the point estimate with the probability information about the sampling point estimate such as the mean to obtain an interval estimate. A sample of 50 safety professionals in the country was used to decide the mean monthly salary of safety professionals.
