Exploratory Data Analysis

Exploratory data analysis (EDA) is an essential step in the data analysis process that helps us understand a dataset's underlying patterns and relationships. In this context, we can use RStudio to perform EDA on the Titanic dataset, which contains information about the passengers on the Titanic and whether they survived or not.

To begin with, we can perform descriptive statistics on the dataset using RStudio's built-in functions like mean, median, standard deviation, and more. This analysis can help us gain insights into the data distribution and identify potential outliers or missing values.

Next, we can use data visualization techniques like scatter plots, histograms, and bar charts to explore the relationships between different variables in the dataset. For instance, we can create a scatter plot to see the relationship between age and fare paid by passengers. Similarly, we can create a histogram to visualize the distribution of passenger ages in the dataset.

Lastly, we can analyze the correlation between variables in the Titanic dataset using correlation analysis techniques. By calculating the correlation coefficient between different variables, we can identify the relationship's strength and direction. For instance, we can determine whether there is a correlation between passenger class and survival rate.