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 >.