help please

Q4 (35 marks) The following data were collected during a study involving patients with cystic brosis. The variable of interest is PEmax (maximum expiratory pressure) which is a good measure of malnutrition. The explanatory variables measured are age, gender, height, weight, BMP, FEV1, FRC, RV and TLC. Several of these variables relate to lung function or body size. The aim of the study is to identify from the possible explanatory variables a model which predicts PEmax well and also to assess how well the 'best model' predicts PEmax. The dataset is saved in the le PEmax.csv and can be downloaded from CANVAS. The dataset contains 11 columns (including subject number which should not be used In analysis) and 52 rows. You will need to download the data file from CANVAS save it onto your drive and then open/copy the data in MINITAB. (i) Flt a multiple regression model to the whole data to identify the explanatory variables that are associated with PEmax, perform a model selection to identify the best model and report the results. (ii) Split the data at random into a Training Set and a Test Set so that you have 40 rows in the Training Set and 12 in the Test Set. Then fit the 'best model' for PEmax based on the training set and test the predictive performance of this model on the Test Set. SH February 2021