- This question targets understanding the various statistical techniques like regression analysis, hypothesis testing, or exploratory data analysis (EDA) that are used to analyze data.
4. **How...
- Addressing data quality issues is crucial, and this question focuses on strategies for dealing with incomplete or unreliable data.
3. **What statistical methods are commonly used in data anal...
- This question explores the overall workflow, from data collection and cleaning to analysis and interpretation of results.
2. **How do you handle missing or inconsistent data in a dataset?
- This question focuses on the decision-making process for choosing appropriate visualizations to effectively communicate data insights.
5. **Can you explain the role of machine learning algori...
- This question delves into the types of statistics used in data analysis and explains how each type serves different purposes.
4. **How do you determine which data visualization techniques to ...
- This question addresses strategies and techniques for dealing with data quality issues, such as missing values, which can affect the results of an analysis.
3. **What are the differences betw...
- This question explores the various stages of data analysis, from data collection and cleaning to analysis and interpretation.
2. **How do you handle missing or incomplete data in a dataset?
What role does machine learning play in modern data analysis, and what are some examples of machine learning algorithms commonly used for data analytics tasks?
