Probability and Statistics QUARTER 3 MASTERY TEST

A random variable is a function that assigns numerical values to:

• Deterministic events

• Random outcomes of an experiment

• Fixed quantities

• Constant values

Which of the following is an example of a discrete random variable?

• The height of students in a class

• The time it takes to run a marathon

• The number of defective items in a batch

• The weight of newborn babies

A continuous random variable is one that:

• Takes a countable number of values

• Has a finite number of possible values

• Can take any value within an interval

• Is always normally distributed

If X represents the number of heads obtained in three tosses of a fair coin, then X is a:

• Continuous random variable

• Discrete random variable

• Neither discrete nor continuous

• Not a random variable

The possible values of a discrete random variable must be:

• Continuous

• Countable

• Unbounded

• Normally distributed

The sum of all probabilities in a probability distribution must equal:

• 0

• 1

• The mean

• The variance

The expected value (mean) of a discrete random variable represents:

• The most frequent value

• The average value over many trials

• The midpoint of possible values

• The maximum probability value

Variance measures:

• The average of all probabilities

• The spread of the random variable

• The highest probability in a distribution

• The expected value of X.

A normal distribution is:

• Asymmetric

• Bell-shaped and symmetric

• Skewed to the left

• Uniform

The total area under a normal curve is:

• 0

• 1

• 100

• Depends on the standard deviation