TAILIEUCHUNG - Lecture Basic statistics for business and economics - Chapter 6: Discrete probability distributions

When you have completed this chapter, you will be able to: Identify the characteristics of a probability distribution, distinguish between a discrete and a continuous random variable, compute the mean of a probability distribution, compute the variance and standard deviation of a probability distribution,. | Discrete Probability Distributions Chapter 06 McGraw-Hill/Irwin Copyright © 2013 by The McGraw-Hill Companies, Inc. All rights reserved. LEARNING OBJECTIVES LO 6-1 Identify the characteristics of a probability distribution. LO 6-2 Distinguish between a discrete and a continuous random variable. LO 6-3 Compute the mean of a probability distribution. LO 6-4 Compute the variance and standard deviation of a probability distribution. LO 6-5 Describe and compute probabilities for a binomial distribution. LO 6-6 Describe and compute probabilities for a Poisson distribution. 6- What is a Probability Distribution? PROBABILITY DISTRIBUTION A listing of all the outcomes of an experiment and the probability associated with each outcome. CHARACTERISTICS OF A PROBABILITY DISTRIBUTION The probability of a particular outcome is between 0 and 1 inclusive. The outcomes are mutually exclusive events. The list is exhaustive. So the sum of the probabilities of the various events is equal to 1. LO 6-1 Identify the characteristics of a probability distribution. 6- What is a Probability Distribution? Experiment: Toss a coin three times. Observe the number of heads. The possible results are: Zero heads, One head, Two heads, and Three heads. What is the probability distribution for the number of heads? LO 6-1 6- Random Variables EXAMPLES The number of students in a class. The number of children in a family. The number of cars entering a carwash in a hour. Number of home mortgages approved by Coastal Federal Bank last week. RANDOM VARIABLE A quantity resulting from an experiment that, by chance, can assume different values. DISCRETE RANDOM VARIABLE A random variable that can assume only certain clearly separated values. It is usually the result of counting something. EXAMPLES The length of each song on the latest Tim McGraw album. The weight of each student in this class. The temperature outside as you are reading this book. The amount of money earned by each

• Kinh tế học
• Basic statistics
• Statistics for business
• Describing data
• Discrete probability distributions
• Probability distribution
• Continuous random variable
• Types of statistics
• Quantitative variables
• Ordinal level data
• Lecture Basic Statistics
• Bài giảng Thống kê cơ bản
• Introduction to Statistics
• Real limits
• Measuring variables
• Correlational studies
• Basic statistics for business
• Basic statistics for economics
• Graphic presentation
• Probability concepts
• Continuous probability distributions
• The central limit theorem
• Confidence intervals
• Two sample tests of hypothesis
• Linear regression
• Multiple regression
• Frequency tables
• Frequency distributions
• Numerical measures
• Sample mean
• Measures of dispersion
• Exploring data
• Dot plot
• Coefficient of skewness
• Joint probability
• Contingency table
• Uniform distribution
• Normal probability distribution
• Sampling methods
• Central limit theorem
• Probability sampling
• Point estimate
• Confidence interval
• One sample tests
• Hypothesis testing
• Test statistic
• Equal variances
• Two sample tests
• Analysis of variance
• Dependent variable
• Independent variable
• Multiple regression analysis
• Multiple linear regression
• Multiple determination
• Nonparametric methods
• Goodness of fit tests
• Contingency table analysis
• Basic business statistics
• Visualizing data
• Basic probability
• The normal distribution
• Other continuous distributions
• Statistical techniques
• Study statistics
• Inferential statistics
• The essentials of statistics
• Basic descriptive statistics
• Ratios and rates
• Central tendency
• The normal curve
• Financial risk management
• Statistics mathematics
• Risk management
• Financial risk
• Financial mathematics
• Some basic math
• Percentile ranks
• The binomial distribution
• descriptive statistics
• basic probability theory
• inductive statistics
• multivariate analysis
• firm understanding
• concise manner
• Conditional probability
• Bayes’ theorem