Analytics SAQL Developer Guide

Overview
Quick Start
Examples
SAQL Reference
SAQL Basic Elements
SAQL Operators
SAQL Statements
SAQL Functions
Aggregate Functions
avg() or average()
count()
first()
last()
max()
median()
min()
sum()
unique()
stddev()
stddevp()
var()
varp()
percentile_cont()
percentile_disc()
regr_intercept()
regr_slope()
regr_r2()
grouping()
Date Functions
Time Zone Date Functions
Work with Custom Fiscal Year Data
String Functions
Math Functions
Windowing Functions
coalesce
Query Performance
PDF

regr_slope()

Uses two numerical fields to calculate a trend line, then returns the slope. Use this function to learn more about the relationship between two numerical fields.
1regr_slope(field_y, field_x)

field_y is a grouped dependent numeric expression and field_x is a grouped independent numeric expression. regr_slope(field_y, field_x) uses simple linear regression to calculate the trend line. The input fields (field_y, field_x) must contain at least two pairs of non-null values. This function works with simple grouped values but not with cogroups.

Example - Calculate the Relationship Between Number of Activities and Deal Amount

Suppose that you have a dataset that includes the number of activities (such as meetings) and the won opportunity amount.

Sample scatter plot.

How much bigger will the deal size be for each extra activity? regr_slope performs a linear analysis on your data then calculates the slope (that is, the increased amount you win for each extra activity).
1q = load "data/sales";
2q = group q by all;
3
4--trunc() truncates the result to two decimal places
5q = foreach q generate trunc(regr_slope('Amount', 'NumActivities'),2) as 'Gain per Activity';

Based on your existing data, every extra activity that you have tends to increase the deal size by $1.45 million, on average.

Diagram showing slope of a regression line.