5. **Can you explain the differences between descriptive, predictive, and prescriptive analytics, and provide examples of when each type would be used?
4. **How do you handle missing or incomplete data in a dataset, and what are the potential consequences of these methods on the analysis results?
3. **What are the common statistical methods used in data analysis, and how do you determine which method is most suitable for your dataset?
2. **How do you choose the appropriate data visualization techniques to effectively communicate your findings to a non-technical audience?
**What are the key steps involved in the data analysis process, and how can each step impact the outcome of an analysis?
5. **How do you select the right statistical methods or algorithms for a given data set, and what factors influence your choice of methodology?
4. **What is the role of data visualization in data analysis, and how do you decide which visualization techniques to use for conveying your findings effectively?
3. **Can you explain the differences between descriptive, diagnostic, predictive, and prescriptive analytics, and provide examples of when each type would be most appropriate to use?
2. **How do you handle missing or incomplete data during an analysis, and what techniques do you use to mitigate any potential biases that missing data might introduce?
**What are the key steps involved in the data analysis process, and how do you ensure the reliability and validity of your data?