Question
Number of shots attempted versus shots made. Interpret the scatterplot by describing any outliers and patterns of clustering.
Basketball Shooting
Shots made
2
1
10
20 3 30
Shots attempted
On your test you will be graded on your short response using the following rubric:
• The answer is correct. The student made no errors while solving.
- The answer shows that the student used problem-solving skills and reasoning.
- All work is shown or explained.
Do you understand how to interpret a scatter plot? Can you explain how you got your answer? Yes or No.
Basketball Shooting
Shots made
2
1
10
20 3 30
Shots attempted
On your test you will be graded on your short response using the following rubric:
• The answer is correct. The student made no errors while solving.
- The answer shows that the student used problem-solving skills and reasoning.
- All work is shown or explained.
Do you understand how to interpret a scatter plot? Can you explain how you got your answer? Yes or No.
Answers
Answered by
GPT-4o mini
Yes, I can explain how to interpret a scatterplot. Let’s break down how to analyze the basketball shooting data in terms of shots attempted versus shots made:
1. **Identify the Axes**: In the given scatterplot, the x-axis represents the number of shots attempted, while the y-axis represents the number of shots made.
2. **Look for Patterns**:
- **General Trend**: Generally, you would expect to see a positive correlation if higher numbers of shots attempted lead to a higher number of shots made.
- **Clusters**: You would look for groups of points that seem to cluster together in certain regions of the plot. For instance, if many players made similar numbers of shots when they attempted around 20 shots, that would show a clustering around that point.
3. **Identify Outliers**:
- Outliers are points that stand apart from the overall distribution. For example, if there’s a player who attempted 30 shots but only made 1 shot, that point would be an outlier because it is significantly lower than expected, given the number of attempts.
- Conversely, if someone attempted a low number like 2 shots but made 10 shots, that might also be considered an outlier, as it would suggest an unusually high shooting efficiency.
4. **Conclusions**:
- You would note any significant observations about how efficiency (shots made per shots attempted) varies across different clusters or outliers. This could provide insights into shooting performance and effectiveness among different players or contexts.
By following this approach, you can draw meaningful conclusions from the scatterplot regarding shooting performance in basketball.
1. **Identify the Axes**: In the given scatterplot, the x-axis represents the number of shots attempted, while the y-axis represents the number of shots made.
2. **Look for Patterns**:
- **General Trend**: Generally, you would expect to see a positive correlation if higher numbers of shots attempted lead to a higher number of shots made.
- **Clusters**: You would look for groups of points that seem to cluster together in certain regions of the plot. For instance, if many players made similar numbers of shots when they attempted around 20 shots, that would show a clustering around that point.
3. **Identify Outliers**:
- Outliers are points that stand apart from the overall distribution. For example, if there’s a player who attempted 30 shots but only made 1 shot, that point would be an outlier because it is significantly lower than expected, given the number of attempts.
- Conversely, if someone attempted a low number like 2 shots but made 10 shots, that might also be considered an outlier, as it would suggest an unusually high shooting efficiency.
4. **Conclusions**:
- You would note any significant observations about how efficiency (shots made per shots attempted) varies across different clusters or outliers. This could provide insights into shooting performance and effectiveness among different players or contexts.
By following this approach, you can draw meaningful conclusions from the scatterplot regarding shooting performance in basketball.