CASE STUDY $-$ ABC Corporation is a retail company that wants to analyze its sales data to understand the relationship between various factors and sales performance. They have collected data on sales revenue, advertising expenditure, store location, and customer demographics over the past few months. The company aims to build predictive models to forecast future sales accurately and make informed decisions about advertising strategies and store expansions.

$1.$What visualization technique would be useful for understanding the relationship between advertising expenditure and sales revenue?

a$.$

Scatter plot

b$.$

Bar chart

c$.$

Line graph

d$.$

Pie chart

$2.$Which metric would be most appropriate for comparing the performance of different regression models in the case study?

a$.$

R$-$squared

b$.$

Mean Absolute Error $($MAE$)$

c$.$

Mean Squared Error $($MSE$)$

d$.$

Root Mean Squared Error $($RMSE$)$

$3.$Which technique aims to identify whether a model is overly complex or overly simplistic based on its performance on unseen data?

a$.$

Model Evaluation

b$.$

Overfitting

c$.$

Underfitting

d$.$

Prediction and Decision Making

$4.$Which technique is used to prevent overfitting in machine learning models?

a$.$

Regularization

b$.$

Model Evaluation

c$.$

Polynomial Regression

d$.$

Simple Linear Regression

$5.$What does a high R$-$squared value indicate in the context of the case study?

a$.$

A large proportion of the variance in sales revenue is explained by the independent variables

b$.$

The model is underfitting

c$.$

The model is overfitting

d$.$

The model is performing poorly