QUESTION TWO

(30 MARKS)

2.1 How do the concepts of median, arithmetic mean, mode, geometric mean, and

harmonic mean play a role in linear regression and Machine Learning, and what are

the differences between these statistical measures in terms of their calculation and

interpretation? Can you provide a comprehensive understanding of each of these

measures, including the pros and cons of each, without relying solely on code or

programming language?

(15)

2.2 How does one use decision trees for making predictions in real-world applications,

and what are the mathematical calculations involved in constructing a decision tree

model? Can you explain the step-by-step process of growing a decision tree, including

the calculation of impurity measures such as Gini index or information gain, and the

use of pruning techniques to improve the model's performance?

(15)