The quantitative approach emphasizes objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques. Key Points Stimulation approach: The simulation approach is a technique that reproduces actual events and processes under test conditions. Developing a simulation is often a highly complex mathematical process. Whenever a new statistical method is developed or used, there are assumptions that need to be tested and confirmed. Statisticians use simulated data to test them out. Inferential approach:: The inferential approach means survey research where a sample of the population is studied (questioned or observed) to determine its characteristics. The basis of hypothesis testing with statistical analysis is inference. Experimental approach: ​The experimental approach to a project involves several items, including the facility used, the model itself, the test conditions where the model is tested, and corrections that are applied to the data. Therefore, the Simulation approach, Inferential approach, and Experimental approach are the approaches that fall under the Quantitative Approach. Additional InformationProjective techniques allow respondents to project their subjective or true opinions and beliefs onto other people or even objects. Depth or in-depth interview is a qualitative research technique that is used to conduct intensive individual interviews where the numbers of respondents are less and research is focused on a specific product, technique, situation, or objective.