Abstract
Data collection is an essential part of the decision making process. In order to avoid subjective variables in the process, it is essential to gather objective information on which the decision will be based on. Sampling is one of the methods that enable to collect data. The aim of this method is to yield some knowledge about the population, by the decision made. For instance, when launching a new advertising campaign, a company needs to gather information on its customers' buying habits, consuming motivators and so on. Sampling is consequently a way to study a smaller, representative sample of the population to gather information. By definition, sampling is "the process of selecting units (e.g., people, organizations) from a population of interest so that by studying the sample we may fairly generalize our results back to the population from which they were chosen."
In this report, we will focus on the key issues regarding "sampling" in the managers' decision making process. After analyzing the different sample selection techniques, we will study the way business managers design strong samples statistically that can be used for multiple purposes. Finally, we will evaluate the way business managers adjust the sample designs so that the samples remain representative as organizational characteristics change over time.
The purpose of this report is to explain how sampling can be used as a reliable tool in the decision making process, even though this process can be endangered by managers' subjectivity and the environmental changes.
