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Any value less than 458 thousand hectares would be hectares IS an outlier. The 3rd quartile is where 75 of the values are below Q3 and 25 are above Q3. Any value greater than 359 thousand hectares would be considered an outlier. Since 331 359 331 thousand hectares is NOT an outlier. Data in Brief 13C 2017 pp. 278-290. Available at http //www. sciencedirect. com/science/article/pii/S2352340917302391 The flow chart to the right shows the general process for timber to become wood pellets. This...

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Step 1: Collect the data for the activity you want to analyze. This data should include the time taken for each activity.

02

Step 2: Calculate the five-number summary for the data. This includes the minimum, maximum, median, and quartiles.

03

Step 3: Plot the box plot using the five-number summary. The plot will consist of a box with two whiskers.

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Step 4: Interpret the box plot. Look for outliers, the spread of the data, and the central tendency.

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Step 5: Use the box plot to compare different activities or analyze the performance of a single activity over time.

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Data scientists who want to explore patterns or trends in activity durations.

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What is activity box plot analysis?

Activity box plot analysis is a statistical method used to visualize the distribution of a dataset and identify potential outliers.

Who is required to file activity box plot analysis?

Businesses or individuals who need to analyze and report on the distribution of their data are required to file activity box plot analysis.

How to fill out activity box plot analysis?

To fill out activity box plot analysis, one must gather the dataset, calculate the quartiles, create the box plot diagram, and analyze any outliers.

What is the purpose of activity box plot analysis?

The purpose of activity box plot analysis is to provide insights into the distribution of data, identify outliers, and compare multiple datasets.

What information must be reported on activity box plot analysis?

On activity box plot analysis, one must report the minimum, first quartile, median, third quartile, maximum, and any potential outliers in the dataset.

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