Overview
This lecture explains how to identify outliers in a dataset using the interquartile range (IQR) method and emphasizes the importance of using computers for calculations with large datasets.
Identifying Outliers with IQR
- Outliers are determined using "1.5 IQR" above and below the quartiles.
- Draw invisible boundaries 1.5 times the IQR from the first and third quartiles.
- Data points outside these boundaries (far left or right) are considered outliers.
- In the provided example, there were two low outliers and no high outliers.
Manual vs. Computer Calculation
- Calculating IQR and outliers by hand works for small datasets.
- For large datasets, use a computer for efficiency and accuracy.
- Computers are essential as data size increases.
Next Steps
- The next lesson will cover using computers for statistical calculations.
Key Terms & Definitions
- IQR (Interquartile Range) — the range between the first (Q1) and third (Q3) quartiles; measures the spread of the middle 50% of data.
- Outlier — a data point that lies outside the 1.5 IQR range from the quartiles.
Action Items / Next Steps
- Prepare to learn how to use computer software for quantitative data analysis in the next lesson.