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6. What is the correct way to write out the normal approximation of Poissan?

  • X ~ N( λ , λ )
  • X ~ Po( λ )
  • X ~ Po( λ , λ )
  • X ~ N( λ , np )

7. What are the conditions required to approximate the binomial using the normal?

  • np > 5 and nq > 5
  • np > 100 and p < 0.1
  • n > 50 and np < 5
  • n > 15

8. What are the conditions needed for an event to modelled using the geometric distribution?

  • independent, constant rate
  • constant probability, occur singly
  • independent, constant probability
  • independent, occur singly

9. What conditions are needed for an event to be modelled using binomial distribution?

  • independent, constant probability
  • random, independent

10. What is the correct way to write out the Poissan approximation of the binomial?

  • X ~ B ( np , λ )
  • X ~ Po( np )
  • X ~ Po( np, λ )
  • X ~ B( np )

11. Which distribution(s) can be used to approximate Poissan?

  • Normal only
  • Binomial and Poissan
  • Poissan only
  • Normal and Geometric

12. If going from a discrete to a continuous distribution, what must you do?

  • Code the Data
  • Cry
  • Continuity Corrections
  • Standardise

13. What are the 4 distributions?

  • Discrete, continuous, partially continuous, direct
  • Geometric, Binomial, Poissan, Normal
  • Geometric, Binomial, Normal, continuous
  • Poissan, Geometric, Normal, Anti-normal

14. What theorem allows the distributions to be approximated using other distributions?

  • The Central Limit Theorem
  • The Theorem of Limitation
  • The Central Theorem
  • The Curved Theorem

15. Which distributions are discrete?

  • Binomial, Poissan, Normal
  • Geometric, Binomial, Poissan
  • Geometric, Binomial
  • Poissan, Normal

16. What are the conditions required to approximate the binomial using Poissan?

  • np > 50 and npq < 5
  • n > 50 and np < 5 OR n > 50 and p < 0.1
  • n > 50 and p < 0.1
  • n > 50 and np < 5