Chris J. Lloyd

Professor of Statistics

I am currently Professor of Business Statistics at University of Melbourne, within the Melbourne Business School.

Most of my research has been on two topics: estimating animal populations using mark recapture; estimation of receiver operating characteristic curves; exact statistic methods. I have 110 peer reviewed papers, mostly single author including Statistics and Computing, Journal of the American Statistical Association, Statistics and Medicine, Biometrics, Journal of the Royal Statistical Society and Journal of Population Research.

I have written a graduate level textbook on categorical data analysis and a lower level textbook on probabilistic decision making and data analysis for MBA students, both published by Wiley.

I have a recent interest in demographic projection of fertility and age curves as well as causal analytics, which I currently teach on the Masters of Business Analytics.

  • NSSS

    This article described the difficulties in providing required sample sizes for clinical trials that guarantee type 1 and type 2 error control. Quoted sample sizes should be based on an efficient and exact test, and the so-called E-test is chosen for this purpose. To compute exact sample sizes in real time is not currently feasible […]

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  • The Case of the Fatal Ratio

    We can all limit our chance of getting Covid. If we get vaccinated and follow the advice about masks and physical distancing, the chance will be much lower. What you and I cannot control is our chance of dying if we get infected. The concept of the case fatality rate (CFR) is apparently straight-forward. If I get infected what is the chance that I die? That’s the bottom line surely. How would we estimate this? By a simple ratio. How many of those infected say one month ago ended up dying? A kid in grade 4 could understand it. When I went to school, we could have calculated it using long-division. Alas, no longer…

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Recent papers


Exact Confidence Limits Compatible with the result of a sequential trial. Journal of Statistical Planning and Inference 207, 171-176.


A comprehensive open-source library for exact required sample size in binary clinical trials. (with E. Ripamonti) Contemporary Clinical Trials 107


Exact confidence limits after a group sequential single arm binary trial. Statistics in Medicine 38, 2389-2399.


Growing rich without growing old: the impact of internal migration in China (with Yip and Chen). Asian Population Studies 16(2), 183-200.


Barnard’s concept of convexity and possible extensions. Reply to the Letter to the Editor (with Ripamonti) Pharmaceutical Statistics 19, 353.