Several factors can influence the likelihood of Type I and Type II errors:
1. Sample Size: Smaller sample sizes generally increase the likelihood of Type II errors. Larger sample sizes can reduce this risk but may increase the chance of Type I errors if not properly controlled. 2. Effect Size: Larger effect sizes are easier to detect, reducing the probability of Type II errors. 3. Significance Level: Lowering the significance level reduces the risk of Type I errors but increases the risk of Type II errors. 4. Variability: Higher variability within the data can increase the probability of both Type I and Type II errors.
