August 17, 2022
Practical steps toward reproducibility
Biography:
Patricia Menéndez is a senior lecturer at the Department of Econometrics and Business Statistics at Monash University Business School. Patricia’s training is in mathematics and Statistics and she received her PhD from ETH Zurich in Switzerland. Since completing her PhD she has held academic positions at Wageningen University, University of New South Wales and University of Queensland. Before joining the department she has also worked outside academia as statistician/ecological statistician for the NSW Bureau of Crime Statistics and Research, and for the Australian Institute of Marine Science.
Patricia has expertise developing and applying statistical methodology and computational methods as well as providing statistical training both in academic and non-academic environments. During her time outside of academia, she has worked on multidisciplinary projects to answer research and policy-making questions in the fields of climate change, environmental and marine sciences besides criminology.
Her research interests include statistical inference, functional data analysis, methods for time series, computational statistics, data visualisation and data science tools.
Talk Overview:
Government organisations, industry players, and universities are embracing the notion of reproducibility around projects involving statistical and data analyses as a cornerstone in their working practices. It has become a basic requirement that projects be built in a reproducible manner to ensure that consistent computational results are obtained when using the same input data, computational methods, code and conditions for analysis. In this talk, I will discuss practical steps that can help managers and data science practitioners to set up their statistics and data analysis projects in a reproducible way. Meanwhile, I will also address some of the fundamental challenges in making work reproducible. I will draw on a few examples from my experience working outside of academia and discuss how reproducibility can be incorporated in university curriculums.