29  Formulating a Research Question

The first and perhaps most crucial step in any data science project is to define a clear, concise, and feasible research question. This question should be specific, measurable, achievable, relevant, and time-bound (SMART). In the context of data science, this often translates to identifying a problem that can be addressed with data-driven solutions.

• Example: If you are working with a retail company, a potential question could be, “Can we predict monthly sales based on historical data?”
• In R: You might start by using exploratory data analysis (EDA) to understand trends, which can be facilitated by packages like ggplot2 for visualization and dplyr for data manipulation.

Poll Time

Q1

You will be provided with a list of potential research questions. Your task is to identify which of these are valid research questions that could feasibly be addressed through a data science project. Select all that you believe are appropriate.

1. What is the best color for a car to ensure high resale value?

2. How does the number of hours spent studying affect students’ final exam scores in introductory data science courses?

3. Can we predict stock prices accurately using historical data?

4. What factors influence a person’s choice of smartphone brand?

5. Which diet is the most effective for weight loss?

6. Do students learn better with online tools than with traditional books?

Access the live poll here: https://PollEv.com/weihongni276