Which regression methods are adequate in proving the following relationship?

Question

I am doing a regression analysis project to answer the question of whether more acidity leads to less chlorides using this data set: http://archive.ics.uci.edu/ml/datasets/Wine+Quality. I first plan on using scatter plots and AV plots to find relationships between chlorides and the predictors (all the other variables in the data set). Then, I plan on transforming the predictors that are important (judgment call) that don't fit linear regression requirements. After that, I plan on using coefficients of determination and partial F-tests to see whether any reduced models are better than the full model (I could be wrong on this). Lastly, I plan on using stepwise regression (forwards and backwards) to find two more models and compare them with whatever model I found in my previous step. My problem is: does my plan actually answer my question? If not, what should I focus more on? Please note that I am only a beginner in regression analysis and the only things that I know include but are not limited to: scatter plots, diagnostic plots, AV plots, t-tests, f-tests, partial f-tests, ANOVA, confidence intervals, p-values, R values, R-squared values, reading R output (summary lm), box-cox transformations, factors. This analysis should be no longer than 5 pages including plots. I would appreciate any feedback.