Project 2

No null values

Both wines data is checked

note: a NULL means that there is no value, we're looking at a blank/empty cell, and 0 means the value itself is 0. So 0 is not considered as a null value

After removing all duplicates in each column in both wine data inly a few rows are survived for red wine, combined data set, a NULL means that there is no value, we're looking at a blank/empty cell, and 0 means the value itself is 0. So 0 is not considered as a null value and no outliers.

By looking into the details, we can see that good quality wines have higher levels of alcohol on average, have a lower volatile acidity on average, higher levels of sulphates on average, and higher levels of residual sugar on average

So, in this data set, the number of independent variables would be 11 (fixed acidity, volatile acidity, citric acid, residual sugar, chlorides, free sulfur dioxide, total sulfur dioxide, density, pH, sulphates, alcohol) as these variables can potentially influence or predict the outcome of the dependent variable "quality."

White wine is more quality than Red wine.