Google Professional Machine Learning Engineer
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In the context of preparing a dataset for machine learning, you are tasked with identifying the most effective method to visualize the distribution of the dataset and detect any potential outliers. The dataset contains numerical values with varying scales and you need to ensure that the visualization method chosen can also facilitate a comparison across different groups within the dataset. Considering the need for a method that is both efficient in terms of computational resources and easy to interpret, which of the following visualization techniques would you choose? (Choose one correct option)
Explanation:
A box plot is the most suitable choice for this scenario because it efficiently summarizes the distribution of numerical data through its quartiles, making it easy to identify the median, spread, and any outliers. It also allows for the comparison of distributions across different groups by placing multiple box plots side by side. While scatter plots (A) are useful for visualizing relationships between two variables, they do not provide as clear a summary of distribution and outliers as box plots. Line graphs (B) are more suited for time series data. Histograms (D) are useful for understanding the frequency distribution of a single variable but do not facilitate easy comparison across groups or clearly highlight outliers as box plots do.