Asian Journal of Probability and Statistics 10(2): 48-58, 2020; Article no.AJPAS.63324 ISSN: 2582-0230 _____________________________________ *Corresponding author: E-mail: eshahriary@miners.utep.edu; Improving Research through Avoiding Common Statistical Errors: The Case of Piosphere Eahsan Shahriary 1* , Thomas E. Gill 1,2 , Richard P. Langford 2 , Musa Hussein 2 , William L. Hargrove 3 and Peter Golding 4 1 Environmental Science and Engineering Program, University of Texas at El Paso, El Paso, Texas 79968, USA. 2 Department of Geological Sciences, University of Texas at El Paso, El Paso, Texas 79968, USA. 3 Center for Environmental Resource Management, University of Texas at El Paso, El Paso, Texas 79968 USA. 4 College of Engineering, University of Texas at El Paso, El Paso, Texas 79968 USA. Authors’ contributions This work was carried out in collaboration among all authors. All authors contributed to the writing of the manuscript. All authors read and approved the final manuscript. Article Information DOI: 10.9734/AJPAS/2020/v10i230244 Editor(s): (1) Dr. Manuel Alberto M. Ferreira, Lisbon University, Portugal. Reviewers: (1) Mohamed Hannabou, University Sultan Moulay Slimane, Morocco. (2) A’Qilah Ahmad Dahalan, National Defence University of Malaysia, Malaysia. Complete Peer review History: http://www.sdiarticle4.com/review-history/63324 Received: 02 October 2020 Accepted: 07 December 2020 Published: 18 December 2020 _______________________________________________________________________________ Abstract For many years scientists studied the piosphere concept- a grazing gradient around a natural/artificial watering point. As is the case for other kinds of ecological studies, the method of statistical analyses applied in many publications is not always appropriate. We note there are many statistical errors and misapplication of data analysis techniques. We reviewed 875 piosphere-related publications between 1915-2018 to find the common statistical methods and common statistical errors in the design of the study, data analyses, presentation of results, and interpretation of study findings. One-way ANOVA, multiple linear regression, Pearson correlation coefficient, permutational multivariate analysis of variance, canonical correspondence analysis, and mean were the most frequent statistical methods applied. Seventy-one common statistical errors in piosphere publications were found. The most common errors were not choosing the proper or appropriate statistical techniques, not checking the assumptions and diagnostics of statistical methods, partial and wrong interpretation of results, and not using informative figures and tables to help readers. Negligence to the proper application of statistics by Original Research Article