Question 2 Two students are looking at data from an investigation and notice some patterns in the data. They create a list of questions they want to investigate to recreate the data on their own. Based on the data, what questions could the students investigate?

Answer 1

To generate meaningful questions based on the data they are observing, the students could consider various aspects of the data patterns. Here are some potential questions they could investigate:

1. Trend Analysis:

   • What trends can we identify over time in the dataset?
   • Are there any noticeable increases or decreases in the data across different time intervals?

2. Correlations:

   • Are there any correlations between different variables in the data? For example, if the data includes variables A and B, do higher values of A correspond with higher or lower values of B?
   • How do changes in one variable affect another variable?

3. Outliers:

   • Are there any outliers in the data, and what might explain these anomalies?
   • How do outliers affect the overall interpretation of the data?

4. Comparative Analysis:

   • How does this dataset compare with another similar dataset?
   • Are there differences in the data based on specific categories (e.g., demographics, location, etc.)?

5. Hypothesis Testing:

   • What hypotheses can we create based on the initial observations of the data?
   • Can we design an experiment to test these hypotheses?

6. Predictive Modeling:

   • Based on the observed patterns, can we predict future data points or trends?
   • What models can we apply to understand or forecast the data behavior?

7. Data Distribution:

   • What is the distribution of the data points? Is it normal, skewed, uniform, etc.?
   • How does the distribution change when different filters or conditions are applied to the data?

8. Factors Influencing the Data:

   • What external factors could be influencing the patterns we observe in the data?
   • How might changes in the environment (social, economic, etc.) affect the data?

9. Methodology:

   • What methods can we use to recreate or collect similar data?
   • How can we ensure the reliability and validity of our new data collection process?

10. Visualization:

    • What visualization techniques can we apply to better understand the patterns in the data (e.g., graphs, charts, heatmaps)?
    • How does visualizing the data change our understanding of what we see?

These questions can guide the students in their investigation and help them recreate data or draw insights from the existing dataset.