title: Presenting parasitological data: the good, the bad and the error bar.
abstract: Visual displays of data in the parasitology literature are often presented in a way which is not very informative regarding the distribution of the data. An example being simple barcharts with half an error bar on top to display the distribution of parasitaemia and biomarkers of host immunity. Such displays obfuscate the shape of the data distribution through displaying too few statistical measures to explain the spread of all the data and selecting statistical measures which are influenced by skewness and outliers. We describe more informative, yet simple, visual representations of the data distribution commonly used in statistics and provide guidance with regards to the display of estimates of population parameters (e.g. population mean) and measures of precision (e.g. 95% confidence interval) for statistical inference. In this article we focus on visual displays for numerical data and demonstrate such displays using an example dataset consisting of total IgG titres in response to three Plasmodium blood antigens measured in pregnant women and parasitaemia measurements from the same study. This tutorial aims to highlight the importance of displaying the data distribution appropriately and the role such displays have in selecting statistics to summarize its distribution and perform statistical inference.
authors.affiliation: Centre for Epidemiology and Biostatistics,Melbourne School of Population and Global Health,The University of Melbourne,207 Bouverie Street,Melbourne,Victoria 3010,Australia.
authors.forename: Sophie G
authors.initials: SG
authors.lastname: Zaloumis
authors.affiliation: Centre for Epidemiology and Biostatistics,Melbourne School of Population and Global Health,The University of Melbourne,207 Bouverie Street,Melbourne,Victoria 3010,Australia.
authors.forename: Freya J I
authors.initials: FJ
authors.lastname: Fowkes
authors.affiliation: Centre for Epidemiology and Biostatistics,Melbourne School of Population and Global Health,The University of Melbourne,207 Bouverie Street,Melbourne,Victoria 3010,Australia.
authors.forename: Alysha
authors.initials: A
authors.lastname: De Livera
authors.affiliation: Centre for Epidemiology and Biostatistics,Melbourne School of Population and Global Health,The University of Melbourne,207 Bouverie Street,Melbourne,Victoria 3010,Australia.
authors.forename: Julie A
authors.initials: JA
authors.lastname: Simpson
mesh_terms: D003196:Computer Graphics; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D010274:Parasitology / Q000706:statistics & numerical data*; D011247:Pregnancy; D011642:Publications; D016008:Statistical Distributions
keywords: Parasitological data; descriptive analysis; display; graph; statistical inference