Box plots, also known as box and whisker plots, are a powerful tool for visualizing statistical data. They can provide insights into the distribution of data, including identifying outliers and showing the spread and central tendency of the data.

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In this article, we’ll discuss how to create a box plot chart in Tableau. We’ll also provide some interview questions and technical round questions related to this topic.

1. Connect to your data source and open a new worksheet.
2. Drag the variable you want to plot on the y-axis to the Rows shelf.
3. Drag a categorical variable to the Columns shelf.
4. Change the mark type to Box Plot.
5. If desired, drag a third variable to the Color shelf to group the data by another variable.
6. Adjust the width of the boxes and the thickness of the lines as desired.

Your box plot chart is now ready to use. You can use the chart to analyze the distribution of data, identify outliers, and compare the spread and central tendency of the data across different categories.

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Box plot charts can be particularly useful for businesses that need to analyze numerical data, such as sales data or financial data. Here are some of the benefits of using box plot charts:

1. Identify outliers: Box plot charts make it easy to identify outliers, or values that are significantly different from the rest of the data. This can be useful for identifying potential errors in the data or for identifying areas where the data is particularly unusual or noteworthy.
2. Analyze distribution: Box plot charts show the distribution of data, including the range of the data, the median, and the interquartile range. This can be useful for identifying patterns or trends in the data, such as whether the data is skewed or whether there are significant differences in the spread of the data across different categories.
3. Compare data across categories: Box plot charts allow businesses to compare the distribution of data across multiple categories at once. This can be useful for identifying areas where one category is significantly different from another, or for comparing the distribution of data across different regions or time periods.

If you’re applying for a data analyst or visualization-related job, you may be asked about your experience creating box plot charts. Here are some potential interview questions:

1. What is a box plot chart, and how is it used?
2. What are the benefits of using a box plot chart over other types of charts or tables?
3. How do you create a box plot chart in Tableau, and what are some of the options for customizing the chart?
4. Can you give an example of a business problem that would be well-suited to analysis using a box plot chart?
5. How would you explain a box plot chart to a non-technical stakeholder?

If you’re asked to demonstrate your Tableau skills in a technical round, you may be asked to create a box plot chart from scratch. Here are some potential technical round questions:

1. Connect to a sample dataset and create a box plot chart that shows the distribution of sales across different product categories.
2. Modify your chart to include subcategories within each product category.
3. Add a filter to your chart that allows users to select a specific region and view the sales data for that region only.
4. Create a calculated field that allows you to compare the distribution of sales data across different time periods, such as month or quarter.

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