Journal Information
Journal ID (publisher-id): BM
Journal ID (nlm-ta): Biochem Med (Zagreb)
Title: Biochemia Medica
Abbreviated Title: Biochem. Med. (Zagreb)
ISSN (print): 1330-0962
ISSN (electronic): 1846-7482
Publisher: Croatian Society of Medical Biochemistry and Laboratory Medicine
Article Information
Copyright statement: ©Croatian Society of Medical Biochemistry and Laboratory Medicine.
Copyright: 2023, Croatian Society of Medical Biochemistry
License (open-access):
This is an Open Access article distributed under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Date received: 22 February 2024
Date accepted: 13 June 2024
Publication date: 05 August 2024
Publication date: 15 October 2024
Volume: 34
Issue: 3
Electronic Location Identifier: 030101
Publisher ID: bm-34-3-030101
DOI: 10.11613/BM.2024.030101
Introducing prediction intervals for sample means
Jeffrey R. Spence[*]
Author notes:
[*] Corresponding author: spencejr@uoguelph.ca
Author contributions
D. Stanely: Conceptualization, Formal analysis, Funding Acquisition, Software, Visualisation, Writing - original draft, Writing - review and editing. J. Spence: Conceptualization, Formal analysis, Funding Acquisition, Visualisation, Writing - original draft, Writing - review and editing. M Contini: Conceptualization, Formal analysis, Visualisation, Writing - original draft, Writing - review and editing.
• Researchers and practitioners are typically familiar with descriptive statistics and statistical inference but may know little about prediction
• We introduce prediction intervals using fundamental concepts that are learned in descriptive and inferential statistical training
• Prediction intervals use a current sample statistic to provide a range (i.e., probabilistic upper and lower bounds) for future sample statistics
• In an applied example, we show how to calculate and interpret a prediction interval
• We use Study 1 sample data to generate a range of values that is likely to contain, a yet to be conducted, Study 2 mean
Researchers and practitioners are typically familiar with descriptive statistics and statistical inference. However, outside of regression techniques, little attention may be given to questions around prediction. In the current paper, we introduce prediction intervals using fundamental concepts that are learned in descriptive and inferential statistical training (i.e., sampling error, standard deviation). We walk through an example using simple hand calculations and reference a simple R package that can be used to calculate prediction intervals.
Keywords: prediction intervals; biostatistics; education; research methodology