Literature DB >> 28622103

The t-test: An Influential Inferential Tool in Chaplaincy and Other Healthcare Research.

Katherine R B Jankowski1, Kevin J Flannelly2, Laura T Flannelly2.   

Abstract

The t-test developed by William S. Gosset (also known as Student's t-test and the two-sample t-test) is commonly used to compare one sample mean on a measure with another sample mean on the same measure. The outcome of the t-test is used to draw inferences about how different the samples are from each other. It is probably one of the most frequently relied upon statistics in inferential research. It is easy to use: a researcher can calculate the statistic with three simple tools: paper, pen, and a calculator. A computer program can quickly calculate the t-test for large samples. The ease of use can result in the misuse of the t-test. This article discusses the development of the original t-test, basic principles of the t-test, two additional types of t-tests (the one-sample t-test and the paired t-test), and recommendations about what to consider when using the t-test to draw inferences in research.

Entities:  

Keywords:  chaplaincy healthcare; inferential statistic; t-test

Mesh:

Year:  2017        PMID: 28622103     DOI: 10.1080/08854726.2017.1335050

Source DB:  PubMed          Journal:  J Health Care Chaplain        ISSN: 0885-4726


  2 in total

1.  Pathogenic Factors Identification of Brain Imaging and Gene in Late Mild Cognitive Impairment.

Authors:  Xia-An Bi; Lou Li; Ruihui Xu; Zhaoxu Xing
Journal:  Interdiscip Sci       Date:  2021-06-09       Impact factor: 2.233

2.  The effect of breast density on the missed lesion rate in screening digital mammography determined using an adjustable-density breast phantom tailored to Japanese women.

Authors:  Mika Yamamuro; Yoshiyuki Asai; Naomi Hashimoto; Nao Yasuda; Yoshiaki Ozaki; Kazunari Ishii; Yongbum Lee
Journal:  PLoS One       Date:  2021-01-07       Impact factor: 3.240

  2 in total

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