Fitness Assessment through Body Fat Prediction
Document Type
Oral Presentation
Campus where you would like to present
SURC Ballroom C/D
Start Date
15-5-2014
End Date
15-5-2014
Keywords
Fitness, Body fat, Regression
Abstract
Health and fitness are important to the students at CWU. Even while attending school, students can still maintain a healthy lifestyle. Fitness is known to be correlated with the amount of body fat a person has. With this as the underlying assumption, the data collected by A. Garth Fisher from Brigham Young University will be used to illustrate a way body fat can be predicted without the traditional visit to the personal trainer or doctor’s office. The data collected included over 250 men and took 18 different measurements of the body including two types of body fat measurement. This study will map the data and find any relationships between body measurements and body fat. By modeling on a small scale and building into a large overall predictive model, the correlations between physical measurements and percentage of body fat will be clear. From those findings, a simple to use equation can be derived to predict body fat based on the input measurements. Through regression analysis the assumptions made using statistical theories will be validated, showing that measuring body fat can be a simple at home process.
For this presentation, Madelyne Weber received a College of the Sciences Best Poster Presentation Award for 2014.
Recommended Citation
Weber, Madelyne, "Fitness Assessment through Body Fat Prediction" (2014). Symposium Of University Research and Creative Expression (SOURCE). 58.
https://digitalcommons.cwu.edu/source/2014/posters/58
Poster Number
49
Additional Mentoring Department
Actuarial Science
Fitness Assessment through Body Fat Prediction
SURC Ballroom C/D
Health and fitness are important to the students at CWU. Even while attending school, students can still maintain a healthy lifestyle. Fitness is known to be correlated with the amount of body fat a person has. With this as the underlying assumption, the data collected by A. Garth Fisher from Brigham Young University will be used to illustrate a way body fat can be predicted without the traditional visit to the personal trainer or doctor’s office. The data collected included over 250 men and took 18 different measurements of the body including two types of body fat measurement. This study will map the data and find any relationships between body measurements and body fat. By modeling on a small scale and building into a large overall predictive model, the correlations between physical measurements and percentage of body fat will be clear. From those findings, a simple to use equation can be derived to predict body fat based on the input measurements. Through regression analysis the assumptions made using statistical theories will be validated, showing that measuring body fat can be a simple at home process.
For this presentation, Madelyne Weber received a College of the Sciences Best Poster Presentation Award for 2014.
Faculty Mentor(s)
Chueh, Yvonne