Red Wine Quality

• Abstract: Use R and apply exploratory data analysis techniques to explore relationships in one variable to multiple variables and to explore the red wine data set for distributions, outliers, and anomalies.

This Red Wine Quality dataset contained 1,599 observations of red wines. There’re 12 variables in the dataset, including 11 variables of chemical properties in these wines, and 1 output variable of wine quality, which graded by experts and is between 0 (very bad) and 10 (very excellent).

I’m interested in exploring how these chemical properties influence the quality of wine with among others. Through univariate, bivariate, multivariate analysis and statistical analysis, I tested different relationships between these variables.

Notes:

This project was completed in an R Markdown formatted file. You can view the HTML output by downloading and opening redwine_Yiyi Tang.html.

Files:

• README.md: this file
• redwine.Rmd: project written in R Markdown format
• improved_redwine_Yiyi Tang.html: improved project report.
• wineQualityReds.csv: data