Why Import Data?

Most real-world data does not come preloaded in R. Data is usually stored in files such as CSV or Excel, which must be imported before analysis.

Importing CSV Files

Explanation:

• read.csv() reads a CSV file
• "data.csv" is the file name (must be in the working directory)
• The dataset is stored in the variable data

To check where R looks for files:

To change the working directory:

Importing Excel Files

Explanation:

• library(readxl) loads the package
• read_excel() reads Excel files
• Useful when working with business datasets

Data Exploration

Understanding Dataset Structure

Explanation:
Shows the first 6 rows to quickly inspect the data.

Explanation:
Displays:

• Number of rows and columns
• Column names
• Data types of each column

Explanation:
Provides statistical summaries like:

• Minimum
• Maximum
• Mean
• Median
• Quartiles

Checking Dimensions

Explanation:
Returns number of rows and columns.

Accessing Columns

Explanation:
Extracts the age column for analysis.

Simple Statistical Analysis

Measures of Central Tendency

Explanation:
Calculates the average score.

Explanation:
Finds the middle value of the data.

Measures of Dispersion

Explanation:
Calculates standard deviation, which shows data spread.

Correlation Analysis

Explanation:
Measures the relationship between age and score:

• Value close to 1 → strong positive relationship
• Value close to -1 → strong negative relationship
• Value close to 0 → weak or no relationship

Basic Visualization

Explanation:
Creates a scatter plot to visually inspect the relationship between two variables.