Discrete Random Variables MBA:4

Question 1

What are the two types of variables?

Answer 1

Discrete and continuous

Question 2

What makes a discrete random variable different?

Examples

Answer 2

Values can be counted or listed
Whole numbers, not fractions

• defective units in a batch
• a listener rating 1 to 5
• students attending a lecture

Things you count

Question 3

What is a continuous random variable?

Answer 3

Variables can be an infinite number of values
Values don’t have to be whole numbers

E.g. weight of a candy box

Things you measure

Question 4

discrete random variable is put in a table or graph or formula that gives the probability associated with each possible value that the variable can assume.

Answer 4

Probability distribution

Question 5

For any value of x in a discrete random variable probability distribution p(x) must be equal or greater than what?

Answer 5

1

Question 6

Expected value or measure of central tendency of a discrete random variable is û

û is -

Answer 6

û is the value expected to occur in the long run and on average

Question 7

What are the characteristics of a binomial distribution (4)

Answer 7

1. There are only 2 possible outcomes
2. Probability remains constant and doesn’t change from trial to trial

3 trials are independent

4. The experiment can be repeated many times

Question 8

What is the formula for a binomial distribution?

Note 0! = 1

Answer 8

p(x)= n!
———— p^x * q^(n-x)
x!(n-x)!

Question 9

If x is a binomial random variable with parameters n and p (so q=1-p), then

• mean =
• Variance =
• Standard deviation =

Answer 9

Mean = n*p

Variance = S^2 x = npq

Standard deviation = Sx = square root npq