My project delves into air quality analysis, specifically focusing on ozone tropospheric (O3) concentration data collected from three different regions in Tunisia. Leveraging R, I conducted a series of tasks to preprocess, analyze, and model the data for meaningful insights.
# Air-Quality-Analysis-Using-R
My project delves into air quality analysis, specifically focusing on ozone tropospheric (O3) concentration data collected from three different regions in Tunisia. Leveraging R, I conducted a series of tasks to preprocess, analyze, and model the data for meaningful insights.
Project Tasks:
Data Import and Cleaning:
Imported project databases and focused on the first three months of 2014.
Eliminated unnecessary data for streamlined analysis.
Data Preprocessing:
Created a new qualitative variable "Mois" based on the Date column.
Detected and managed outliers in the dataset.
Explored and addressed missing values, proposing a method for imputation.
Data Normalization:
Scaled variables as needed, justifying choices for normalization.
Univariate Analysis:
Conducted a comprehensive univariate analysis, summarizing statistics and visualizing data distributions.
Bivariate Analysis:
Explored correlations between variables using appropriate hypothesis tests, with a focus on the relationship between O3 and other variables.
Linear Regression:
Performed simple and multiple linear regression analyses to understand the relationship between O3 and other variables.
Developed a strategy to enhance the regression model's performance.
Reduced dimensionality using principal component analysis.
Generalized Additive Models (GAM):
Conducted a literature review on GAM models.
Implemented GAM models to understand the relationship between O3 and explanatory variables.