Lecture 12- Random Variables

Question 1

What is a random variable?

Answer 1

The outcome is not deterministic or computer like. In other words you get a different answer every time and it is unpredictable e.g. coin toss

Question 2

What variable type (continuous, discrete, categorical) is a random variable?

Answer 2

Any of the three

Question 3

With random variables what happens as increase the sample size?

Answer 3

The relative frequency (fi/n) of each outcome (xi) stabilizes to give the probabilities for each outcome. These set of probabilities forms the probability distribution.

Question 4

For a categorical or discrete probability distribution what do all values sum to?

Answer 4

1

Question 5

What is a statistical model?

Answer 5

A mathematical description of the way the data are generated.
It’s like a metaphor/ rough guide of what will happen

Question 6

What two values do we find in order to describe discrete or continuous probability distributions?

Answer 6

• Mean

- Variance or standard deviation

Question 7

What is µX?

Answer 7

The mean of X

Question 8

What is σ^2x?

Answer 8

The variance of x

Question 9

Refer to slides and work through examples of how to calculate mean, variance and standard deviation

Question 10

Refer to slides to look at how to combine random variables…

Question 11

How are random variables represented?

Answer 11

By upper case roman letters