COM726 Support - Week 2

Research Question

Research Question

A research question is a clear, focused, and specific inquiry that guides a research study. It is a crucial component of the research process as it helps define the scope and purpose of the study. A well-formulated research question helps researchers identify what information they need to gather, analyse, and interpret in order to address their research objectives.

A research question should be:

  1. Clear: It should be easily understandable and free from ambiguity.
  2. Focused: It should have a specific scope, avoiding overly broad or vague inquiries.
  3. Relevant: It should align with the topic of investigation and contribute to existing knowledge or address a gap in understanding.
  4. Feasible: It should be realistically answerable within the constraints of the available resources, time, and methodology.
  5. Interesting: It should be intellectually stimulating and hold significance for the field of study.

A well-crafted research question guides the entire research process, including the selection of research methods, data collection, analysis, and interpretation of results. It helps researchers stay focused and ensures that their study generates meaningful and valuable insights.

For example, a research question in the field of psychology could be: “What is the relationship between sleep deprivation and cognitive performance in university students?” This question specifies the variables of interest (sleep deprivation and cognitive performance) and the population under investigation (university students), providing a clear direction for the study.

Example for a Data Science Project:

“What is the relationship between customer satisfaction and online reviews for a specific e-commerce platform, and can sentiment analysis of these reviews be used to predict customer satisfaction levels?”

This research question focuses on exploring the connection between customer satisfaction and online reviews in the context of an e-commerce platform. The goal is to investigate whether sentiment analysis, a natural language processing technique, can be applied to predict customer satisfaction levels based on the content of the reviews.

This question could guide the data science project, which would involve collecting and analysing a dataset of customer reviews and associated satisfaction ratings. The project may include tasks such as sentiment analysis, feature extraction, model training, and evaluation to determine the predictive power of online reviews in estimating customer satisfaction.

For a good overview and glossary Machone Learing and Data Science go to:

C3.AI, 2023. Glossary of data-science [viewed 3 July 2023]. Available from: https://c3.ai/glossary/data-science/model-training/