Correlation, Causation, Bias, and Variance

In this chapter, we will delve into some fundamental statistical concepts, correlation, causation, bias, and variance. Understanding these terms isn’t just academic; it’s essential for applying Artificial Intelligence (AI) in the real-world domain of cybersecurity. Why? Knowing the difference between correlation and causation can help you make informed decisions while understanding bias and variance is crucial for building robust models.

In this chapter, you’ll learn the following:

• The definitions of correlation and causation, and why mistaking one for the other can lead to significant errors in cybersecurity
• How bias and variance affect your AI models, and why managing them is key to developing effective security systems
• Practical strategies to identify and mitigate these issues in your cybersecurity efforts

By the time you finish this chapter, you’ll have a solid grasp of these critical...