MLS-C01 Question #373: Real Exam Question with Answer & Explanation

Question

A machine learning (ML) specialist collected daily product usage data for a group of customers. The ML specialist appended customer metadata such as age and gender from an external data source. The ML specialist wants to understand product usage patterns for each day of the week for customers in specific age groups. The ML specialist creates two categorical features named dayofweek and binned_age, respectively. Which approach should the ML specialist use discover the relationship between the two new categorical features?

Options

• ACreate a scatterplot for day_of_week and binned_age.
• BCreate crosstabs for day_of_week and binned_age.
• CCreate word clouds for day_of_week and binned_age.
• DCreate a boxplot for day_of_week and binned_age.

Explanation

To discover the relationship between two categorical features like 'dayofweek' and 'binned_age', crosstabulations are the most appropriate visualization and analysis approach.

Common mistakes.

• A. A scatterplot is used to visualize the relationship between two numerical variables and is not suitable for analyzing the relationship between two categorical features.
• C. Word clouds are used for visualizing the frequency of words in text data and are irrelevant for understanding the relationship between numerical or categorical features.
• D. A boxplot is typically used to display the distribution of a numerical variable across different categories of a categorical variable or to compare distributions, not to directly show the relationship between two categorical features.

Concept tested. Exploratory Data Analysis - Categorical features

Reference. https://docs.aws.amazon.com/sagemaker/latest/dg/data-wrangler-analyze.html

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