his dataset contains the data for 150 subjects. The following are the variables of interest: vo2max_pre: estimated peak VO2 before cardiac rehabilitation age: age in years . bmi: body mass index . hoursSit: hours spent sitting per day We are interested in determining whether the subjects' vo2max_pre can be predicted from the other variables bove. To do this, we will use the dataset to determine the best multiple regression model, check all regression ssumptions, and report the results. Use a 5% significance level for this entire problem set. (3 points) In SPSS, create a correlation table and find the correlation of vo2max_pre with each of the other 3 variables. Organize the variables (name, r) in the chart below from the strongest to the weakest correlation with vo2max_pre. Put a star (*) above all the variables which have significant correlations with vo2max_pre. You do not need to include the correlation table in your Brightspace submission. Tariable Correlation strongest weakest Vote: Although there are multiple ways to choose the best multiple regression model, we will start with the full model and delete variables one at a time. Make sure to include in your Brightspace submission your ANOVA ables, model summaries, and coefficients tables for each model in questions 2-3