using RStudio :

winequality file available online , provide code, and answers

1. Load the winequality-red.csv data file.

2. Inspect the data by looking at the first few entries and the last few entries in the dataset as well as the variable types. In particular, we are interested in predicting the "quality" of the red wine, by knowing the "total.sulfur.dioxide" content of the wine.

1. Generate descriptive statistics. Evaluate these descriptives and print them here.

2. Make a scatter plot of the relationship between "quality" and "total.sulfur.dioxide". Does it look like the relationship is best fit by a straight line or perhaps something curvilinear?

3. Run a series of polynomial multiple regression models with "quality" as your outcome that includes "total.sulfur.dioxide" as a predictor. Start with a linear model, then add a quadratic term, then run another model that includes a cubic term. Compare the results of the models.

a. Report the results here in APA format. Be sure to include the adjusted R2 value, the b estimates, and the p-values. What can you conclude from your results and which model best characterizes this relationship?