1. Probability Distributions – Finite RV’s Random variables first introduced in Expected Value def. A finite random variable is a random variable that can assume only a finite number of distinct values Example: Experiment-Toss a fair coin twice X( random variable)- number of heads X can assume only 0, 1, 2

2. Probability mass function

3. Probability mass function(p.m.f)- Small f

5. Cumulative distribution function(c.d.f)

6. Cumulative distribution function(c.d.f)- Big F

8. Calculating Probabilities-Using p.m.f & c.d.f

11. p.m.f

12. Expected value –Finite R.V

23. Probability Distributions – Continuous RV’s

24. Probability density function-p.d.f

25. p.d.f

27. Relationship between Probability & Area of p.d.f - for Continuous R.V

29. Important

31. c.d.f

35. Uniform random variable

36. p.d.f for uniform random variable

37. c.d.f for uniform random variable

38. Expected value for uniform random variable

39. Example for Uniform random variable

40. Graph of p.d.f for uniform

41. Graph of c.d.f for uniform

46. Exponential random variable

47. p.d.f/c.d.f/ expected value – Exponential random variable