# EXAMPLE - Statistical Functions

This example illustrates how you can apply statistical functions to your dataset. Calculations include average (mean), max, min, standard deviation, and variance.

Functions:

Item

Description

AVERAGE Function

Computes the average (mean) from all row values in a column or group. Input column can be of Integer or Decimal.

MIN Function

Computes the minimum value found in all row values in a column. Input column can be of Integer, Decimal or Datetime.

MAX Function

Computes the maximum value found in all row values in a column. Inputs can be Integer, Decimal, or Datetime.

VAR Function

Computes the variance among all values in a column. Input column can be of Integer or Decimal. If no numeric values are detected in the input column, the function returns 0.

STDEV Function

Computes the standard deviation across all column values of Integer or Decimal type.

NUMFORMAT Function

Formats a numeric set of values according to the specified number formatting. Source values can be a literal numeric value, a function returning a numeric value, or reference to a column containing an Integer or Decimal values.

MODE Function

Computes the mode (most frequent value) from all row values in a column, according to their grouping. Input column can be of Integer, Decimal, or Datetime type.

Source:

Students took a test and recorded the following scores. You want to perform some statistical analysis on them:

Student

Score

Anna

84

Ben

71

Caleb

76

Danielle

87

Evan

85

Faith

92

Gabe

85

Hannah

99

Ian

73

Jane

68

Transformation:

You can use the following transformations to calculate the average (mean), minimum, and maximum scores:

 Transformation Name New formula Single row formula AVERAGE(Score) 'avgScore'
 Transformation Name New formula Single row formula MIN(Score) 'minScore'
 Transformation Name New formula Single row formula MAX(Score) 'maxScore'

To apply statistical functions to your data, you can use the VAR and STDEV functions, which can be used as the basis for other statistical calculations.

 Transformation Name New formula Single row formula VAR(Score) var_Score
 Transformation Name New formula Single row formula STDEV(Score) stdev_Score

For each score, you can now calculate the variation of each one from the average, using the following:

 Transformation Name New formula Single row formula ((Score - avg_Score) / stdev_Score) 'stDevs'

Now, you want to apply grades based on a formula:

standard deviations from avg (stDevs)

A

stDevs > 1

B

stDevs > 0.5

C

-1 <= stDevs <= 0.5

D

stDevs < -1

F

stDevs < -2

You can build the following transformation using the IF function to calculate grades.

 Transformation Name New formula Single row formula IF((stDevs > 1),'A',IF((stDevs < -2),'F',IF((stDevs < -1),'D',IF((stDevs > 0.5),'B','C'))))

To clean up the content, you might want to apply some formatting to the score columns. The following reformats the stdev_Score and stDevs columns to display two decimal places:

 Transformation Name Edit column with formula stdev_Score NUMFORMAT(stdev_Score, '##.00')
 Transformation Name Edit column with formula stDevs NUMFORMAT(stDevs, '##.00')
 Transformation Name New formula Single row formula MODE(Score) 'modeScore'

Results:

Student

Score

modeScore

avgScore

minScore

maxScore

var_Score

stdev_Score

stDevs

Anna

84

85

82

68

99

87.00000000000001

9.33

0.21

C

Ben

71

85

82

68

99

87.00000000000001

9.33

-1.18

D

Caleb

76

85

82

68

99

87.00000000000001

9.33

-0.64

C

Danielle

87

85

82

68

99

87.00000000000001

9.33

0.54

B

Evan

85

85

82

68

99

87.00000000000001

9.33

0.32

C

Faith

92

85

82

68

99

87.00000000000001

9.33

1.07

A

Gabe

85

85

82

68

99

87.00000000000001

9.33

0.32

C

Hannah

99

85

82

68

99

87.00000000000001

9.33

1.82

A

Ian

73

85

82

68

99

87.00000000000001

9.33

-0.96

C

Jane

68

85

82

68

99

87.00000000000001

9.33

-1.50

D