T-test:

• What it is: Like the Z-test, but used when the population variance is unknown.
• Types:
  • One-sample t-test: Compare the mean of a single sample to a known value.
  • Two-sample t-test: Compare the means of two different samples.
  • Paired t-test: Compare the means of the same group at different times (e.g., stock prices before and after a significant event).
• Assumptions: Assumes data is approximately normally distributed, and samples have similar variances (for the two-sample t-test).
• Use case: Suppose you have two trading strategies and you want to know which one has a higher average return. You'd collect a sample of returns from both strategies and use a two-sample t-test to see if there's a significant difference between them.