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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