7.5.2.1.2 Type I and Type II Errors

• What does a Type I error imply in hypothesis testing?

  It suggests a false positive result
• How does a Type I error relate to chance in research findings?

  It occurs due to random luck in results
• What does a Type II error signify in a study?

  Missing a real effect when it's present
• What is a Type II error?

  Accepting the null hypothesis when it's false
• What is a Type I error?

  Rejecting the null hypothesis when it's true
• In a study testing an exercise program, what would a Type II error indicate?

  The program helps, but results show no improvement
• What is the consequence of lowering the p-value threshold?

  Increases risk of Type I error
• Why is it important to minimize Type I errors?

  It prevents wasting resources on ineffective treatments
• How are Type I and Type II errors related?

  One type's avoidance increases the other's risk
• How is a Type II error also referred to?

  False negative
• What is a Type I error in psychological research?

  Claiming a false positive result
• What happens if a security system is set to be very sensitive?

  Increases Type I error risk
• What is the significance of minimizing Type I and Type II errors in research?

  To ensure findings are accurate and useful
• What is a Type II error?

  Missing real effects, delaying advancements
• What are Type I and Type II errors in hypothesis testing?

  Errors in hypothesis testing
• In a study testing a new drug, what would a Type I error indicate?

  The drug appears effective when it isn't
• Why is it important to minimize Type II errors?

  It ensures effective interventions are recognized and adopted
• What are the impacts of Type I and Type II errors?

  • Type I: False positive results
  • Promotes ineffective treatments
  • Wastes resources
  • Type II: False negative results
  • Delays recognition of effective interventions
  • Potentially harms people
• How do Type I and Type II errors balance in research?

  • Balancing errors provides reliable information
  • Benefits society by ensuring accurate findings
  • Helps in recognizing effective treatments
• How can understanding Type I and Type II errors improve research design?

  • Helps in selecting appropriate sample sizes
  • Aids in choosing correct statistical tests
  • Enhances reliability of study conclusions
• What is a Type I error?

  False conclusions, like promoting ineffective treatments
• What are the consequences of a Type I error in research?

  Wasting resources and misleading people
• What is a potential outcome of a Type II error in research?

  Missing valuable treatment opportunities
• What is a Type II error in psychological research?

  Failing to detect a true effect
• What are the key differences between Type I and Type II errors?

  • Type I Error:
  • Rejecting a true null hypothesis
  • Results in a false positive
  • Risk increases when lowering p-value threshold

  
  

  • Type II Error:
  • Accepting a false null hypothesis
  • Results in a false negative
  • Risk increases when raising p-value threshold
• What are the key differences between Type I and Type II errors?

  • Type I Error: False positive, claims effect exists when it doesn't
  • Type II Error: False negative, fails to detect effect when it does