Amity Science, Technology & Innovation Foundation (ASTIF) organised a webinar on the topic "Overview of Quantitative Analysis". Dr. Parul Kumar, Senior Assistant Professor, Maharaja Agrasen Institute of Management Studies, GGSIPU shared her views on the topic. The webinar aimed to enlighten the faculty members, researchers and students regarding the quantitative methods which ca be used for data interpretation thereby increasing the chances of getting research articles published in Journals of repute.
Sharing her views, Dr. Parul Kumar said quantitative research is a systematic & scientific investigation of data and their relationships. It help in developing mathematical models, theories and hypothesis. It emphasizes objective measurements and statistical, mathematical or numerical analysis of data collected through polls, questionnaires, or by manipulating pre-existing statistical data using computational techniques. Quantitative research help in understanding of an occurrence or association, it works for large samples whereas qualitative research helps in understanding the nature or quality of phenomenon with small samples. Quantitative analysis examine the relationship between independent variables, dependent variables and extraneous variables. Descriptive, correlational, cause- comparative and experimental researches are four types of quantitative research. She explained the process of Quantitative Research are stated the steps on follow:
Step1- Make observation about something unknown, unexplained or new
Step 2- Hypothesize the explanation for those observations
Step 3- Make a prediction of outcome based on you hypothesis
Step 4- Formulate the plan to test the prediction
Step 5- Verifying the findings, draw conclusions & relate with literature
Quantitative Research produces clear results but it also has various limitations associated with it. It gives non- context insights because the focus is numerical, can lead to overlooking broader themes and relationships. It can be misleading or subjective, opinions and bias occur earlier in the process. It has lack of inability to control the environment. It is a difficult, expensive and requires a lot of time in data collection and analysis, said Dr Parul.