Data Analytics with Python Week 10 NPTEL Assignment Answers 2025

NPTEL Data Analytics with Python Week 10 Assignment Answers 2024

1. Sampling distribution for a goodness of fit test is the

Options:
a. Poisson distribution
b. t distribution
c. normal distribution
d. chi-square distribution

✅ Answer: d
Explanation: Chi-square distribution is used because it compares observed and expected frequencies, making it suitable for categorical data in a goodness-of-fit test.

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2. Goodness of fit test is always conducted as a

Options:
a. lower-tail test
b. upper-tail test
c. middle test
d. None of these alternatives is correct

✅ Answer: b
Explanation: It is an upper-tail test since we are interested in whether the test statistic is large enough to reject the null hypothesis, indicating significant deviation.

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3. State True or False: Statement: Null hypothesis for chi square test of independence assumes that, all the proportions are equal.

Options:
a. True
b. False

✅ Answer: a
Explanation: The chi-square test of independence assumes no association between variables, implying proportions are equal across categories.

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4. Statistical test conducted to determine whether to reject or not reject a hypothesized probability distribution for a population is known as a

Options:
a. contingency test
b. probability test
c. goodness of fit test
d. None of these alternatives is correct

✅ Answer: c
Explanation: Goodness-of-fit test is used to assess whether the observed data fits a specified distribution.

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5. What is the minimum no. of variables/features required to perform clustering?

Options:
a. 0
b. 1
c. 2
d. 3

✅ Answer: b
Explanation: Even with one feature, clustering can be performed, though clustering is more useful with multiple features.

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6. Which of the following method is used for finding optimal clusters in K-Mean algorithm?

Options:
a. Elbow method
b. Manhattan method
c. Euclidian method
d. None of these

✅ Answer: a
Explanation: Elbow method helps determine the optimal number of clusters by plotting WCSS and finding the “elbow” point where improvement drops.

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7. Movie Recommendation systems are an example of

Options:
a. 2 Only
b. 1 and 2
c. 1 and 3
d. 1, 2, 3 and 4

✅ Answer: d
Explanation: Recommendation systems use Classification (user preference), Clustering (user groups), Reinforcement Learning (learning over time), and Regression (rating prediction).

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8. How can Clustering (Unsupervised Learning) be used to improve the accuracy of the Linear Regression model (Supervised Learning):

Options:
a. 1 Only
b. 1 and 2
c. 1 and 4
d. 1, 2, 3 and 4

✅ Answer: d
Explanation: All listed strategies (cluster-based models, using cluster ID, centroids, and sizes) can enhance regression model performance.

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9. Let x₁ = (1,2) and x₂ = (3,5) be the coordinates for two objects. The Euclidean and Manhattan distance between these two objects is __ respectively

Options:
a. 4.2 and 3
b. 3.15 and 2
c. 3.61 and 5
d. None of these

✅ Answer: c
Explanation:

• Euclidean = √[(3–1)² + (5–2)²] = √13 ≈ 3.61
• Manhattan = |3–1| + |5–2| = 2 + 3 = 5

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10. State true or false: Discriminant Analysis does not require the grouping variable to be known at the beginning

Options:
a. True
b. False

✅ Answer: b
Explanation: Discriminant Analysis is supervised and requires prior knowledge of the grouping (class) variable to build a classification model.