Obtain K so that it is the joint probability mass function;
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
![(i) Attempt the following questions. Show all necessary steps. Read
the questions carefully. (ii) Any copied material from internet or
your class fellows will get you ZERO marks.
Q. 1 Let X be the number of bugs in the first draft of a piece of software,
and let Y be the number of bugs remaining in the second draft of the same
software. Their joint probability mass function is given by the following
table:
Y
0.
1
3
0.
0.03
0.14
0.09
0.08
1
0.05
0.10
K
0.04
0.04
0.09
0.08
0.09
(i) Obtain K so that it is the joint probability mass function;
(ii) Find cumulative distribution function Fyy (x, y);
(iii) Find the following probabilities using cdf obtained above (a) P(X <
3, Y < 2), (b) P(XY > 4), (c) P(X + Y > 3), (e) P(X < 3,Y < 2)
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