Skip to content
Free planNo credit card requiredStart writing

article · The Korean Journal of Measurement and Evaluation in Physical Education and Sports Science · 2007

A cross validation study of developing regression model for estimation of % body fat from body mass index

JungHwanCho

Cited by 1Abstract and details only

Abstract

The index has no abstract for this paper. The publisher’s page may have one.

Cite this paper

APA 7

JungHwanCho. (2007). A cross validation study of developing regression model for estimation of % body fat from body mass index. The Korean Journal of Measurement and Evaluation in Physical Education and Sports Science, 9(1), 75–85. https://doi.org/10.21797/ksme.2007.9.1.006

MLA 9

JungHwanCho. “A cross validation study of developing regression model for estimation of % body fat from body mass index.” The Korean Journal of Measurement and Evaluation in Physical Education and Sports Science, vol. 9, no. 1, 2007, pp. 75–85, https://doi.org/10.21797/ksme.2007.9.1.006.

Chicago

JungHwanCho. 2007. “A cross validation study of developing regression model for estimation of % body fat from body mass index.” The Korean Journal of Measurement and Evaluation in Physical Education and Sports Science 9 (1): 75–85. https://doi.org/10.21797/ksme.2007.9.1.006.

Harvard

JungHwanCho (2007) ‘A cross validation study of developing regression model for estimation of % body fat from body mass index’, The Korean Journal of Measurement and Evaluation in Physical Education and Sports Science, 9(1), pp. 75–85. Available at: https://doi.org/10.21797/ksme.2007.9.1.006.

BibTeX
@article{junghwancho2007cross,
  title = {{A cross validation study of developing regression model for estimation of % body fat from body mass index}},
  author = {JungHwanCho},
  journal = {The Korean Journal of Measurement and Evaluation in Physical Education and Sports Science},
  volume = {9},
  number = {1},
  pages = {75--85},
  year = {2007},
  doi = {10.21797/ksme.2007.9.1.006}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.