Correlation analysis in ML Python - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding Pearson Correlation Coefficient

Which statement correctly describes the Pearson correlation coefficient between two variables?

A It measures the difference in means between two groups.

B It measures the probability that two variables are independent.

C It measures the strength and direction of a linear relationship between two continuous variables.

D It measures the total variance explained by a regression model.

❓ Predict Output

intermediate

Output of Correlation Calculation in Python

What is the output of the following Python code?

ML Python

import numpy as np
x = np.array([1, 2, 3, 4, 5])
y = np.array([2, 4, 6, 8, 10])
correlation = np.corrcoef(x, y)[0, 1]
print(round(correlation, 2))

A -1.00

B 0.80

C 0.00

D 1.00

❓ Model Choice

advanced

Choosing Correlation Method for Nonlinear Data

You have two variables with a clear nonlinear but monotonic relationship. Which correlation method is best to measure their association?

A Spearman rank correlation coefficient

B Chi-square test

C Mean squared error

D Pearson correlation coefficient

❓ Metrics

advanced

Interpreting Correlation Matrix Output

Given the correlation matrix below, how many pairs of variables have a strong positive correlation (above 0.7)?

   A    B    C    D
A  1.0  0.8  0.3  0.6
B  0.8  1.0  0.5  0.9
C  0.3  0.5  1.0  0.2
D  0.6  0.9  0.2  1.0

A 3

B 2

C 4

D 1

🔧 Debug

expert

Debugging Correlation Calculation Code

What error does the following Python code raise?

import numpy as np
x = [1, 2, 3]
y = [4, 5]
correlation = np.corrcoef(x, y)[0, 1]
print(correlation)

A ValueError due to different lengths of x and y

B IndexError due to accessing [0, 1] in a 1D array

C TypeError because lists cannot be used with np.corrcoef

D No error, prints correlation value