Show simple item record

dc.contributor.authorTorres-Valcárcel, Angel R.;Gonzalez-Avilés, Cesar
dc.date.accessioned2018-01-03T11:00:00Z
dc.date.available2018-01-03T11:00:00Z
dc.date.copyright6/29/2017 12:00:00 AM
dc.date.issued2017
dc.identifier.otherei-d-16-0018.1.pdf
dc.identifier.urihttp://138.201.223.254:8080/yetl1/handle/yetl/4245858
dc.description.abstractAbstractThe 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.
dc.publisherAmerican Meteorological Society
dc.titleComments on “Short-Term Precipitation and Temperature Trends along an Elevation Gradient in Northeastern Puerto Rico”
dc.typeJournal Paper
dc.journal.volume21
dc.journal.issue6
dc.journal.titleEarth Interactions
dc.identifier.doi10.1175/EI-D-16-0018.1
dc.journal.fristpage1
dc.journal.lastpage4
dc.treeEarth Interactions:;2017:;volume( 021 ):;issue: 006
dc.contenttypeFulltext


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record