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Google Professional Machine Learning Engineer

Google Professional Machine Learning Engineer

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In the context of Exploratory Data Analysis (EDA), a data scientist is tasked with analyzing a dataset containing sales data over the past year to identify trends and relationships. The dataset includes continuous variables such as 'Sales Amount' and 'Number of Items Sold'. Which of the following visualizations would be most effective for the data scientist to use to explore the relationship between these two continuous variables, and why? (Choose one correct option)

Real Exam

Explanation:

Correct Option: B. A scatter plot to visualize the relationship between 'Sales Amount' and 'Number of Items Sold'

Explanation: Scatter plots are the most effective tool for visualizing the relationship between two continuous variables. They allow the data scientist to see how 'Sales Amount' varies with 'Number of Items Sold', identifying potential correlations, outliers, or patterns. This is crucial for understanding the underlying trends in the sales data.

Why other options are incorrect:

  • A. A bar chart to summarize the sales amount by category: Bar charts are better suited for comparing categorical data, not for exploring relationships between continuous variables.
  • C. A pie chart to show the proportion of sales by item category: Pie charts are used to show parts of a whole for categorical data, not for analyzing relationships between continuous variables.
  • D. A line graph to track the sales amount over time: Line graphs are ideal for showing trends over time but do not help in exploring the relationship between two continuous variables like 'Sales Amount' and 'Number of Items Sold'.
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