How to Remove Outliers in R: A Quick Guide

Outliers can skew your data analysis. Here’s a quick guide on how to remove outliers in R:

1. **Identify Outliers:** Use the `boxplot()` function to visualize and identify outliers.

boxplot(your_data$variable)

2. **Calculate IQR:** Compute the Interquartile Range (IQR) to determine outlier thresholds.

iqr <- IQR(your_data$variable)

3. **Define Limits:** Establish the upper and lower bounds to identify outliers.

upper_bound <- quantile(your_data$variable, 0.75) + 1.5 * iqr
lower_bound <- quantile(your_data$variable, 0.25) - 1.5 * iqr

4. **Remove Outliers:** Filter out the outliers from your dataset.

filtered_data <- your_data[your_data$variable > lower_bound & your_data$variable < upper_bound, ]

By following these steps, you ensure cleaner, more accurate data for your analysis in R.