•The probability can be greater than 1

•A variable can be qualitative or quantitative, wherein the latter can be either discrete or continuous.

•In a probability distribution for a discrete random variable, the sum of all the probabilities must be greater than one. 

•In a probability distribution for a discrete random variable, the sum of all the probabilities must be greater than one. 

•Suppose a manager mandates that all male employees must measure between 64 and 74 inches in height.

•The height of a person is a continuous variable.

•If the mean of a discrete random variable X is zero, then all the values of X must also be zero.

•The probability mass function (PMF) is used to describe the probability distribution of a continuous random variable.

•A random variable is a numerical outcome of a random experiment.

•A random variable can only take on discrete values.

•The standard deviation of a probability distribution measures the spread of the distribution around its mean.

•The variance of a random variable measures the spread or dispersion of its probability distribution.

••If you multiply a random variable by a constant, the variance of the resulting random variable is equal to the square of the constant times the original variance.

•A negative z-score tells that the raw value it corresponds to is below the mean

•The height of a normal distribution curve determines the probability for normally distributed variables.

•A probability distribution is the mathematical function that gives the probabilities of occurrence of different possible outcomes for an experiment.

•A continuous random variable can take on any value within a given range.

•More than 50% of the area of the entire curve of a standard normal distribution is enclosed by the z- scores; z=-1 and z=1. 

•The daily temperature in Baguio City is an example of a continuous random variable.

•The normal curve is symmetrical about the mode.

•If the variance of a random variable is zero, then all outcomes of the random variable must be the same.

• It is a quantitative variable whose value can only be attained through counting.

• It is a variable whose value is dependent on the outcome of well-defined event or experiment.

•I•It is a random variable that can assume measurable values.

•Which of the following is not a property of the standard normal distribution?

•Which of the following is not a random variable?

•It reveals how many units of the standard deviation the raw score x is above or below the mean.

•If Andrei’s score is 87, the class average is 82, and the SD is 4, what is Andrei's Z-score?

•According to the empirical rule, how much of the data falls within 2 standard deviations?

•What does the z-score represent in a normal distribution?

•Find the area under the normal distribution curve that represents the area to the left of Z =-2.37.

•Find the variance of the following discrete probability distribution

X = -1, 0, 1

P(x) = 0.1, 0.8, 0.1

On an exam in Statistics and Probability, the grades are normally distributed with a mean of 76 and a standard deviation of 10.

Find the grade corresponding to z=-0.50

In a college entrance exam, the average score of 1,000 test takers is 150 with a standard deviation of 5. Assuming the scores are normally distributed, what is the probability that the student will get a score above the mean?

•What is the standard deviation of the probability distribution? Write your answer on two decimal places.

X = 1 3 5 7 9

P(x) = 0.15 0.35 0.05 0.16 0.29