Answer Happy

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