Probability Distribution

XG
by Xuan Geng4 views·Updated Nov 29, 2021

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  1. the second type of distribution that we're going to talk about is
  2. the nominal distribution.
  3. His definition is the probability distribution
  4. associated with the discrete random bearable.
  5. It's called a phenomenal probability distribution.
  6. And we will introduce this kind of distribution to you by two perspectives.
  7. The first one is his properties and then we will introduce the property
  8. function and use one marketing related example to give it a practice.
  9. And there are four points about the problem
  10. practice of phenomenal distribution.
  11. The first one there should be an identical trials.
  12. Then the two outcomes are possible on a trail. For example, success or failure,
  13. the property of a success or failure
  14. does not change
  15. the final is the trials are independent.
  16. Um If you need to remember this for private properties of phenomenal distribution,
  17. the simplest example is coin tossing
  18. when they come see the phenomenal privacy function which is shown below
  19. um where PX echoes to the probability of x successes and trials
  20. and and pursue the number of trials
  21. and pie. It can sue. The probability of a success on anyone trial,
  22. then y minus pi. It comes to the probability of failure
  23. of anyone trial.
  24. Then let's use the example of marine closing store to um practice this function.
  25. Let's consider the purchase decisions of the next
  26. three customers who entered the marine clothing store.
  27. On the basis of past experience.
  28. The store manager estimates the probability that any
  29. one customer will make a purchase is 3.3.
  30. So the pie should be equal to 3.3 other situation.
  31. So the problem is what is the property that two
  32. of the next three customers will make a purchase?
  33. So obviously in this situation, the total trails through the three
  34. and the success trials tribute to
  35. And uh hi echoes to 2.3. So put this number into the function.
  36. We can calculate
  37. the probability that two of the next three customers making the purchase
  38. Is .189.
  39. Similarly,
  40. we can calculate um zero or one or three of the next three cosmos making the purchase
  41. and adding this for province. Together we get the total property.
  42. It goes to one.