exploring stratified sampling: July 31, 2020

concept

• Match the distribution of a feature in one group to another by selective sampling.
  
• In our case we sample from a comparison pool to form a comparison group in which the distributions of one or more key consumption parameters are statistically matched to a treatment group. 

Stratifying a sample is done based on binning: Bins are defined based on the treatment group. The relative number of customers between treatment and comparison groups needs to match in every bin.

anticipated strategy

For most comparison pools, stratify on up to 3 parameters

1. Annual Consumption
2. Percent usage change from COVID
3. 3. A parameter of relevance to the program (likely a normalized metric)

Examples of normalized electric features

% Heating kWh

% Baseload kWh

% Summer Peak kWh

Video of the July 31, 2020 Meeting: Comparison WG VIDEO - 2020-07-31
Slides from the July 31, 2020 Meeting (cumulative): Comparison WG SLIDES - 2020-07-31
Chat Record from the July 31, 2020 Meeting: Comparison WG Chat - 2020-07-31