Distribution analysis (box plots) in Tableau - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a box plot by dragging the correct mark type.

Tableau

Drag the mark type to [1] to create a box plot visualization.

Drag options to blanks, or click blank then click option'

ALine

BBar

CBox-and-Whisker

DCircle

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing 'Bar' or 'Line' mark types which do not show distribution quartiles.

Selecting 'Circle' which is used for scatter plots.

The Box-and-Whisker mark type is used in Tableau to create box plots, which show distribution, median, quartiles, and outliers.

2fill in blank

medium

Complete the calculation to find the median value for the box plot.

Tableau

Create a calculated field with the formula: MEDIAN([1])

Drag options to blanks, or click blank then click option'

A[Sales]

BSUM([Sales])

CAVG([Sales])

DCOUNT([Sales])

Attempts:

3 left

💡 Hint

Common Mistakes

Using aggregated functions like SUM or AVG inside MEDIAN which causes errors.

Using COUNT which counts rows, not values.

The MEDIAN function requires a field, so use the field name [Sales] directly to calculate the median sales value.

3fill in blank

hard

Fix the error in the calculation to exclude null values from the box plot.

Tableau

IF NOT ISNULL([1]) THEN [Profit] END

Drag options to blanks, or click blank then click option'

A[Profit]

BISNULL([Profit])

CAVG([Profit])

DSUM([Profit])

Attempts:

3 left

💡 Hint

Common Mistakes

Using aggregated functions inside the IF which causes errors.

Using ISNULL inside the THEN clause which is incorrect.

The condition checks if the field is not null, so inside the IF statement you should use the field [Profit] directly to return the value for non-null rows.

4fill in blank

hard

Fill both blanks to create a calculated field that identifies outliers beyond 1.5 times the interquartile range.

Tableau

IF [Profit] [1] ([Q3] + 1.5 * [2]) THEN 'Outlier' ELSE 'Normal' END

Drag options to blanks, or click blank then click option'

A>

BIQR

CQ1

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' for detecting upper outliers.

Using Q1 instead of IQR in the multiplication.

Outliers are values greater than Q3 plus 1.5 times the interquartile range (IQR). So the condition uses > and IQR.

5fill in blank

hard

Fill all three blanks to create a calculated field that classifies data points as 'Lower Outlier', 'Upper Outlier', or 'Normal'.

Tableau

IF [Sales] [1] ([Q1] - 1.5 * [2]) THEN 'Lower Outlier' ELSEIF [Sales] [3] ([Q3] + 1.5 * IQR) THEN 'Upper Outlier' ELSE 'Normal' END

Drag options to blanks, or click blank then click option'

A<

BIQR

C>

DQ1

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up comparison operators for lower and upper outliers.

Using Q1 instead of IQR in the multiplication.

Lower outliers are values less than Q1 minus 1.5 times IQR, so use < and IQR. Upper outliers are values greater than Q3 plus 1.5 times IQR, so use >.

Practice

1. What does a box plot primarily show in data visualization?

easy

A. The total count of data points

B. The spread of data including median, quartiles, and outliers

C. Only the average value of the data

D. The correlation between two variables

Solution

1. Step 1: Understand box plot components

   A box plot displays the median, quartiles (Q1 and Q3), and any outliers in the data.

2. Step 2: Compare options to definition

   Only the spread of data including median, quartiles, and outliers correctly describes these features; others describe different charts or statistics.

3. Final Answer:

   The spread of data including median, quartiles, and outliers -> Option B

4. Quick Check:

   Box plot = median + quartiles + outliers [OK]

Hint: Box plots show data spread, not just averages [OK]

Common Mistakes:

• Confusing box plots with bar charts
• Thinking box plots show only averages
• Ignoring outliers in box plots

2. Which Tableau feature helps you quickly create a box plot?

easy

A. Using the 'Show Me' panel and selecting box plot

B. Writing a custom SQL query

C. Using the Data Interpreter tool

D. Applying a filter on the data source

Solution

1. Step 1: Identify Tableau tools for visualization

   Tableau's 'Show Me' panel offers quick chart types including box plots.

2. Step 2: Evaluate other options

   Custom SQL, Data Interpreter, and filters do not create visualizations directly.

3. Final Answer:

   Using the 'Show Me' panel and selecting box plot -> Option A

4. Quick Check:

   'Show Me' = quick box plot creation [OK]

Hint: Use 'Show Me' to pick box plot instantly [OK]

Common Mistakes:

• Confusing data preparation tools with visualization tools
• Trying to write SQL for box plots in Tableau
• Thinking filters create charts

3. Given a box plot in Tableau showing sales by region, what does the line inside the box represent?

medium

A. The average sales value

B. The maximum sales value

C. The median sales value

D. The total sales sum

Solution

1. Step 1: Recall box plot components

   The line inside the box is the median, which divides data into two equal halves.

2. Step 2: Differentiate median from average and extremes

   The average is the mean, not shown by the line; max is the whisker end; total sum is not shown.

3. Final Answer:

   The median sales value -> Option C

4. Quick Check:

   Box plot line = median [OK]

Hint: Median is the line inside the box, not average [OK]

Common Mistakes:

• Confusing median with average
• Thinking the line shows max or total
• Ignoring box plot whiskers

4. You created a box plot in Tableau but the whiskers are missing. What is the most likely cause?

medium

A. You forgot to add a measure to the Rows shelf

B. The data contains no outliers or extreme values

C. The data source is not connected

D. You applied a filter that removed all data

Solution

1. Step 1: Understand box plot requirements in Tableau

   Box plots need a measure on Rows or Columns to calculate quartiles and whiskers.

2. Step 2: Analyze each option

   No whiskers usually mean no measure is assigned; data connection or filters removing all data would prevent any plot.

3. Final Answer:

   You forgot to add a measure to the Rows shelf -> Option A

4. Quick Check:

   Missing whiskers = no measure assigned [OK]

Hint: Always add a measure to Rows or Columns for box plots [OK]

Common Mistakes:

• Assuming no whiskers means no outliers only
• Ignoring the need for measures in visualization
• Not checking data connection status

5. You want to compare sales distributions across multiple product categories using box plots in Tableau. Which approach best ensures clear comparison?

hard

A. Filter data to one category at a time and view box plots

B. Create separate worksheets for each category and compare manually

C. Use a pie chart to show sales proportions per category

D. Place product category on Columns and sales measure on Rows, then select box plot from 'Show Me'

Solution

1. Step 1: Set up box plot for multiple categories

   Placing product category on Columns and sales on Rows allows Tableau to create side-by-side box plots for comparison.

2. Step 2: Evaluate other options

   Separate worksheets or filtering one category at a time prevents direct visual comparison; pie charts do not show distribution.

3. Final Answer:

   Place product category on Columns and sales measure on Rows, then select box plot from 'Show Me' -> Option D

4. Quick Check:

   Side-by-side box plots = best for category comparison [OK]

Hint: Use Columns for categories and Rows for measure to compare box plots [OK]

Common Mistakes:

• Using pie charts instead of box plots for distribution
• Comparing categories in separate sheets
• Filtering to one category losing comparison context