Python Assessment: Multivariate Analysis :Understanding and Visualizing Data with Python (Statistics with Python Specialization) Answers 2025
1. Question 1
Is the relationship between ‘Height’ and ‘Wingspan’ linear?
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✅ Yes
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❌ No
Explanation:
In the Cartwheel dataset, height and wingspan are strongly positively correlated, showing a clear linear relationship.
2. Question 2
Is the relationship between ‘Wingspan’ and ‘Height’ linear for each gender?
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❌ Yes
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✅ No
Explanation:
When split by gender, the linear pattern weakens and becomes inconsistent across groups, so it is not clearly linear for each gender.
3. Question 3
Is the interquartile range (IQR) of ‘CWDistance’ similar to ‘Wingspan’?
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❌ Yes
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✅ No
Explanation:
The spread (IQR) of CWDistance is much larger and more variable compared to Wingspan, so they are not similar.
4. Question 4
Looking at the barplot of ‘Glasses’ and ‘CWDistance’, which group has a slightly larger cartwheel distance?
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❌ Glasses-Y
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✅ Glasses-N
Explanation:
The no-glasses group (Glasses-N) shows a slightly higher average CWDistance.
5. Question 5
Barplot of ‘Glasses’ and ‘CWDistance’ split by gender — which condition has a larger estimate?
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❌ Glasses-Y
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❌ Glasses-N
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✅ The results are different for each gender.
Explanation:
When separated by gender, one gender shows slightly higher distance for glasses-Y while the other shows higher for glasses-N. So the pattern is not consistent.
🧾 Summary Table
| Q# | Correct Answer | Key Concept |
|---|---|---|
| 1 | Yes | Height–Wingspan is linear |
| 2 | No | Not linear when split by gender |
| 3 | No | IQRs differ significantly |
| 4 | Glasses-N | Slightly higher CWDistance |
| 5 | Different for each gender | Interaction effect |