contributor author | Torres-Valcárcel, Angel R.;Gonzalez-Avilés, Cesar | |
date accessioned | 2018-01-03T11:00:00Z | |
date available | 2018-01-03T11:00:00Z | |
date copyright | 6/29/2017 12:00:00 AM | |
date issued | 2017 | |
identifier other | ei-d-16-0018.1.pdf | |
identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4245858 | |
description abstract | AbstractThe selection of statistical methods to evaluate data depends on study questions and characteristics of available data. In climate science, some methods are more popularly used than others; however, the use of applicable alternative methods does not invalidate study findings. Regardless of limitations, some methods like Pearson ordinary correlation are widely used in all sciences including climate and by scientists at government agencies like NOAA and the USGS. In addition, the use of the robust Student?s t test is valid for near-Gaussian distributions with high sample numbers, since it is resistant to data distribution inconsistencies. We wish to put in context the citation about our article and clarify the methods and justification for using them and to educate readers about the use of some conventional statistical tools and tests. | |
publisher | American Meteorological Society | |
title | Comments on “Short-Term Precipitation and Temperature Trends along an Elevation Gradient in Northeastern Puerto Rico” | |
type | Journal Paper | |
journal volume | 21 | |
journal issue | 6 | |
journal title | Earth Interactions | |
identifier doi | 10.1175/EI-D-16-0018.1 | |
journal fristpage | 1 | |
journal lastpage | 4 | |
tree | Earth Interactions:;2017:;volume( 021 ):;issue: 006 | |
contenttype | Fulltext | |