tailieunhanh - Lecture Statistical techniques in business and economics - Chapter 6: Discrete probability distributions

When you have completed this chapter, you will be able to: Define the terms probability distribution and random variable; distinguish between discrete and continuous random variables; calculate the mean, variance, and standard deviation of a discrete probability distribution; describe the characteristics and compute probabilities using the Poisson probability distribution. | Chapter 6 Discrete Probability Distributions 1. Define the terms probability distribution and random variable. 2. Distinguish between discrete and continuous random variables. 3. Calculate the mean, variance, and standard deviation of a discrete probability distribution. 4. Describe the characteristics and compute probabilities using the Poisson probability distribution. Chapter Goals When you have completed this chapter, you will be able to: Terminology Random Variable is a numerical value determined by the outcome of an experiment. Probability Distribution is the listing of all possible outcomes of an experiment and the corresponding probability. Discrete Types of Probability Distributions Under this distribution the random variable has a countable number of possible outcomes Under this distribution the random variable has an infinite number of possible outcomes Continuous Examples Discrete Continuous Examples Students in a class Number of children in a family Types of Probability | Chapter 6 Discrete Probability Distributions 1. Define the terms probability distribution and random variable. 2. Distinguish between discrete and continuous random variables. 3. Calculate the mean, variance, and standard deviation of a discrete probability distribution. 4. Describe the characteristics and compute probabilities using the Poisson probability distribution. Chapter Goals When you have completed this chapter, you will be able to: Terminology Random Variable is a numerical value determined by the outcome of an experiment. Probability Distribution is the listing of all possible outcomes of an experiment and the corresponding probability. Discrete Types of Probability Distributions Under this distribution the random variable has a countable number of possible outcomes Under this distribution the random variable has an infinite number of possible outcomes Continuous Examples Discrete Continuous Examples Students in a class Number of children in a family Types of Probability Distributions Mortgage Loan Number of Mortgages approved in a month Distance driven by an executive to get to work The length of time of a particular phone call The length of time of an afternoon nap! Distinguishing features of a Discrete Distribution: The sum of the probabilities of the various outcomes is The probability of a particular outcome is between 0 and The outcomes are mutually exclusive Consider a random experiment in which a coin is tossed three times Q uestion Heads Let x be the number of Tails Let T represent the outcome of Let H represent the outcome of a Head Determine the probability distribution Listing the possibilities Heads Heads Heads Tails Heads Heads Tails Heads Heads Tails Heads Heads Tails Heads Tails Tails Heads Tails Tails Tails Tails the possible values of x (number of heads) are 0,1,2,3. Tails Heads Tails Consider a random experiment in which a coin is tossed three times. Determine the probability distribution. Q uestion Probability .

• Kinh tế học
• Statistical techniques
• Statistical techniques in business
• Statistical techniques in economics
• Descriptive statistics
• Discrete probability distributions
• Continuous random variables
• Statistical inference
• Independent samples
• Statistical process control
• Quality management
• Random observation
• Sampling methods
• Central limit theorem
• Confidence intervals
• Point estimator
• Confidence interval
• Hypothesis testing
• Alternative hypothesis
• Analysis of variance
• F distribution
• Linear regression
• Coefficient of correlation
• Multiple regression
• Multiple regression analysis
• Chi square applications
• Test of hypothesis
• Analysis of ranked data
• Kruskal Wallis test
• Index numbers
• Consumer price index
• Time series
• Linear trend equation
• Decision making
• Organize information
• The role of statistics
• Qualitative variable
• Describing data
• Frequency distribution
• Central tendency
• Standard deviation
• Ungrouped data
• Probability concepts
• Random experiment
• Decision theory
• Decision alternative
• Inferential statistics
• Frequency tables
• Numerical measures