Open AccessExplanation of BMI data using Linear Regression Model in R
Author(s) -
Sukhvir Singh
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.40640
Subject(s) - underweight , statistic , linear regression , statistics , overweight , regression analysis , mathematics , regression , residual , medicine , body mass index , algorithm
This paper describes the regression analysis between different variable like Weight & BMI, Weight & Height, and Height & BMI using Linear Regression Model & data visualization techniques in R Programming from a sample data of 68 students of BCA. The collected data were analyzed for underweight, overweight, obese personalities by using conditional statements. The result of the model will give Residual Standard Error, Multiple R2 , Adjusted R2 , F-statistic and p-value. There is visualization of data using ggplot() and geom() in last steps. Keywords: BMI, Multiple R2 , Adjusted R2 , F-statistic, p-value, R, ggplot, geom.