could someone help me out with this problem its been a real

could someone help me out with this problem, it\'s been a real hassle

Body Fat from Linear Regression. Excess adiposity is a risk factor for a range of diseases, leading to increased morbidity and mortality. Body fat (BF) can be measured by several techniques such as skin-fold measurements bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DEXA). Most of these techniques are not used in the clinical practice or they arc not adequate when large populations arc considered. Fuster-Para ct al. (2015)^2 compare several linear models for predicting the body fat (BF) from Age, Body Mass Index (BMI), Body Adiposity Index (BAI) and Gender. Data set RegBF.dat I mat I xlsx provides data on Age (in years), Body Adiposity Index (BAI), Body Mass Index (BMI), Body Fat (BF). and Gender (0 for males and 1 for females), of 3,200 adults from Mallorca (Spain). Percentage of body fat mass was obtained by Tetrapolar Bioclcctrical Impedance Analysis (BIA) system (BF-350, Tanita Corp, Tokyo. Japan). The BAI is defined as hip circumference in cm / (height in m)^1.5 - 18. We are interested in predicting BF from Age, BAI, BMI, Gender, and BB. BB is a new variable defined as 3B = 3AI .* BKI, and as such, describes the interaction between BAI and BMI. Construct variable BB and form a design matrix X consisting of columns Age, BAI, BMI, Gender, and BB. Suggest two models: first with a single best predictor, and the second with 3 best predictors. You can use stepwise in the process. A new person is to be evaluated using the two models from (b). The covariates arc: Age = 35, BAI = 26, BMI = 20, Gender = 0. BB - 520. What arc the predicted BF\'s from the two models. For the first model with a single best oovariatc, find the 95% prediction interval, when that covariate is as in (c).

Solution

its a simple linear regression model, or you can model the body fat by two way anova model with interaction. B.F will be a dependent variable and the others like BAI, BB,age,BMI,gender will be the independent set of variables. In any statistical software if you put the sample values of the variables and do a multiple linear regression model, it will give you the estimates of the coefficients, which variables are more significant and their order of importance. It\'s a one minute task to perform all the calculations. there are several packages folr stepwise regression. But everything can be done if and only if you give the sample data set. Otherwise no statistical software can do the calculation.

Please upload the dataset in excel format, or you follow the procedure I have instructed, then you will get all the results, including the confidence interval also.