Statistics Final Year Topic: Distinguishing Hurdle and Zero-Inflated Models in Simulated Count Data

This Statistics final year project uses simulated count datasets with explicitly specified zero and positive-count mechanisms to investigate a specific question in mixture models. The analysis is designed around known generating conditions so that the behaviour of competing statistical procedures can be checked.

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Why choose this project topic?

This study makes excess zeros an explicit, reproducible comparison. Working with simulated count datasets with explicitly specified zero and positive-count mechanisms lets you separate the target quantity from its estimate and explain when a statistical conclusion depends on assumptions.

How do hurdle and zero-inflated models differ in fitting zeros and positive counts under known generating processes?

Agree the scenario ranges, sample sizes and reporting measures for excess zeros before running the study.

Proposed project objectives

01Specify the data-generating conditions for simulated count datasets with explicitly specified zero and positive-count mechanisms.
02Implement a reproducible analysis of excess zeros with documented software settings.
03Evaluate the estimates and uncertainty relevant to this question: How do hurdle and zero-inflated models differ in fitting zeros and positive counts under known generating processes?

A suggested research approach

Generate data separately from each model family and compare fitted zero probabilities and positive-count predictions. Track identifiability and convergence problems rather than reporting only a fit statistic. Write the analysis before inspecting favourable runs, record random seeds where simulation is used, and keep generated study data distinct from observed field data.

What you will need

A written design for simulated count datasets with explicitly specified zero and positive-count mechanisms
Statistical software supporting mixture models and reproducible scripts
A supervisor-agreed range of scenarios and computational budget

Keep your project scope clear

Similar fit to observed counts may not identify whether zeros arise from a separate structural process.

Statistics project chapter outline

Use this outline as a starting point. You can edit the chapter titles to match your department’s format during setup.

Chapter 1Introduction
Chapter 2Literature Review
Chapter 3Theory and Methodology
Chapter 4Results and Applications
Chapter 5Summary, Conclusion and Recommendations

Turn this topic into your own final year project.

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