Quantitative Research Methodology (online)

The Research Methodology Training Program provides faculty, researchers, and students with the tools necessary to conduct high-quality, consequential studies and to apply research methodology principles to the unique obstacles and prospects posed by deep tech innovation.

In the world of deep tech, where new ideas come from using data, it is very important to understand basic research methodology ideas to make sure that the results are reliable and true. Understanding the research process is important for handling the complicated nature of deep tech projects in a planned way, from coming up with clear research questions to sharing results in a useful way. Using research designs that are specific to deep tech projects lets researchers do rigorous and accurate tests and observational studies, which is important for getting reliable results. Sampling techniques and sample size determination
methods make it easier to collect data, which makes sure that study results are accurate and can be applied to the whole deep tech field.

Maintaining validity, reliability, and ethical behavior throughout the study process is also very important in high-tech fields where choices can have huge effects. Researchers protect the validity of their results and build trust in the deep tech community by following ethical standards and minimizing biases. New ways of collecting data use the power of new technologies to collect large, varied datasets. These datasets give researchers the building blocks they need to fuel deep tech innovation. Effective communication strategies make it easier for study results to reach the right people, which encourages collaboration and the sharing of knowledge within the deep tech ecosystem.