Statistical sampling methods have been the new discovery in the fields of survey and data analysis. Unlike earlier times where sample analysis was done by collecting data from the entire population, today, random sampling have become the new face of data analysis. Sampling methods such as these are used to extract key information regarding something and helps the researcher to draw inferences based on them.
A data analysis also includes quantitative modeling of historical data to determine the future behavior of the population and to estimate profits and losses. The results conjectured from these sample analysis very much depends on the researcher and on the methods which he used to carry out the survey. A well planned and designed analysis can be very less time consuming and may yield precise and accurate results. It also makes the job of the researcher much easier when it comes to the drawing of inferences.
A statistical inference in basically done to validate the assumption or the hypotheses made by the researcher. Inferences are drawn to ensure the success or failure of the survey done. Inferences can be of different types, such as the ‘Bayesian inference’ or the frequentest inference, both of which are the results of the data analysis done.