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Null Model - Meaning & Definition

Published by MBA Skool Team in Statistics Last Updated: November 21, 2023Read time:

What is Null Model?

Null Model is a model generated with random samples of a specific distribution where certain elements are constant and others are allowed to vary stochastically. Null model helps in specifying a statistical distribution or randomization of the observed data, designed to predict the outcome of a random process without specifying all of its parameters.

Null model graph is used to match some randomly generated graph, and is believed to be similar until it is proven otherwise. Null Hypothesis is discussed under null model which states that no statistical significance exists in a given set of observations until a statistical evidence nullifies it for an alternate hypothesis. Null models form an intermediary between statistical null hypothesis (one obtained through theories) and Mechanistic models (one obtained through process with all parameters)



Consider a null model with 1 degree of freedom and a log-likelihood of -8024. Similarly assume alternative model with 3 degrees of freedom and a log-likelihood of -8012. Then the probability of its difference is, chi squared value of +2(8024-8012)=24 with 3-1=2 degrees of freedom. Later on by following certain assumptions, chi squared distribution is followed and hence p value is computed.

This article has been researched & authored by the Business Concepts Team which comprises of MBA students, management professionals, and industry experts. It has been reviewed & published by the MBA Skool Team. The content on MBA Skool has been created for educational & academic purpose only.

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