- 3-1 Random Variables and Probability Distribution of a Discrete Random Variable, p. 179
- define, and use in context, the following key terms: random variable; discrete random variable and continuous random variable; probability distribution of a discrete random variable
- Random variables
- Discrete random variable
- Continuous random variable
- construct a probability distribution in table or graph form, given a discrete random variable defined for an experiment.
- Probability distribution of a discrete random variable
- use a probability distribution to find the probabilities of various simple and compound events.
- 2 Characteristics of a probability distribution
- 3-2 Mean and Standard Deviation of a Discrete Random Variable, p. 187
- define, and use in context, the following key terms: mean of a discrete random variable; standard deviation of a discrete random variable
- Mean of a discrete random variable
- Standard deviation of a discrete random variable
- compute the mean and standard deviation of a discrete random variable.
- 3-3 The Binomial Probability Distribution, p. 193
- define, and use in context, the following key terms: conditions of a binomial experiment; binomial distribution; mean and standard deviation of a binomial distribution
- The binomial experiment
- conditions of a binomial experiment
- construct a binomial probability distribution, given a binomial experiment.
- The binomial probability distribution and binomial formula
- compute probabilities associated with a binomial experiment, using the binomial formula, a binomial table, or both.
- compute the mean and standard deviation for a binomial distribution.
- Mean and standard deviation of the binomial distribution
- Using the table of binomial probabilities
- Probability of success and the shape of the binomial distribution
Hypergeometric probability distributionPoisson distributions
- 3-4 The Standard Normal Distribution, p. 227
- identify and use the two characteristics of a continuous probability distribution: the probability that x assumes a value within a given interval lies between 0 and 1; the sum of the probabilities for the value of x is equal to 1.
- compute probabilities for a standard normal distribution.
- Continuous probability distribution
- identify and use the 3 properties of a normal distribution: the total area under the curve of a normal distribution is equal to 1; the curve is symmetrical about the mean; the tails of the curve extend indefinitely.
- The normal distribution
- The standard normal distribution
- 3-5 The Normal Distribution, p. 240
- explain the concept of z values or z scores, and determine and interpret z values.
- Standardizing a normal distribution
- converting an x value to a z
- compute probabilities for any normal distribution, given the mean and standard deviation.
- Applications of the normal distribution
- determine the z and x values for a normal distribution, when an area under the normal curve is known.
- Determining the z and x values when an area under the normal distribution curve is known
- 3-6 The Normal Approximation to the Binomial Distribution, p. 255
- define, and use in context, the term "continuity correction factor"
- Continuity correction factor
- use the standard normal distribution table to approximate probabilities for binomial distributions when the sample size is very large.
- Normal distribution as an approximation to binomial distribution
normal quantile plots