tailieunhanh - Lecture Business statistics in practice (7/e): Chapter 5 - Bowerman, O'Connell, Murphree

Chapter 5 - Discrete random variables. After mastering the material in this chapter, you will be able to: Explain the difference between a discrete random variable and a continuous random variable, find a discrete probability distribution and compute its mean and standard deviation, use the binomial distribution to compute probabilities,. | Chapter 5 Discrete Random Variables Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Discrete Random Variables Two Types of Random Variables Discrete Probability Distributions The Binomial Distribution The Poisson Distribution (Optional) The Hypergeometric Distribution (Optional) Joint Distributions and the Covariance (Optional) 5- Two Types of Random Variables Random variable: a variable that assumes numerical values that are determined by the outcome of an experiment Discrete Continuous Discrete random variable: Possible values can be counted or listed The number of defective units in a batch of 20 A listener rating (on a scale of 1 to 5) in an AccuRating music survey Continuous random variable: May assume any numerical value in one or more intervals The waiting time for a credit card authorization The interest rate charged on a business loan LO5-1: Explain the difference between a discrete random . | Chapter 5 Discrete Random Variables Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Discrete Random Variables Two Types of Random Variables Discrete Probability Distributions The Binomial Distribution The Poisson Distribution (Optional) The Hypergeometric Distribution (Optional) Joint Distributions and the Covariance (Optional) 5- Two Types of Random Variables Random variable: a variable that assumes numerical values that are determined by the outcome of an experiment Discrete Continuous Discrete random variable: Possible values can be counted or listed The number of defective units in a batch of 20 A listener rating (on a scale of 1 to 5) in an AccuRating music survey Continuous random variable: May assume any numerical value in one or more intervals The waiting time for a credit card authorization The interest rate charged on a business loan LO5-1: Explain the difference between a discrete random variable and a continuous random variable. 5- Discrete Probability Distributions The probability distribution of a discrete random variable is a table, graph or formula that gives the probability associated with each possible value that the variable can assume Notation: Denote the values of the random variable by x and the value’s associated probability by p(x) LO5-2: Find a discrete probability distribution and compute its mean and standard deviation. 5- Discrete Probability Distribution Properties For any value x of the random variable, p(x) 0 The probabilities of all the events in the sample space must sum to 1, that is LO5-2 5- The Binomial Distribution The binomial experiment characteristics Experiment consists of n identical trials Each trial results in either “success” or “failure” Probability of success, p, is constant from trial to trial The probability of failure, q, is 1 – p Trials are independent If x is the total number of successes in n .

• Quản trị kinh doanh
• Business Statistics
• Business statistics in practice
• Descriptive statistics
• Discrete random variables
• Discrete probability distributions
• Binomial distribution
• Lecture Business statistics
• Bài giảng Thống kê doanh nghiệp
• Descriptive statistics tabular
• Descriptive statistics graphical presentations
• Summarizing quantitative data
• Essentials of modern business statistics
• Modern business statistics
• Graphical presentations
• numerical measures
• Exploratory data analysis
• Interval estimation
• Hypothesis tests
• Simple linear regression
• Basic statistics
• Statistics for business
• Describing data
• Types of statistics
• Quantitative variables
• Ordinal level data
• Data sources
• Statistical inference
• Illustrate sampling
• Graphical methods
• Tabular methods
• Graphically summarizing qualitative data
• Numerical methods
• Describing central tendency
• Measures of variation
• Sample spaces
• Elementary probability rules
• Compute conditional probabilities
• Continuous random variables
• Continuous probability distributions
• Uniform distribution
• Sampling distributions
• Random sampling
• Stratified random
• Confidence intervals
• Sample size determination
• Hypothesis testing
• Alternative hypotheses
• Sampling distribution
• Equal variance
• Statistical inferences
• Population variances
• Experimental design
• Analysis of variance
• Randomized block design
• Chi square tests
• Chi square goodness of fit tests
• Multinomial experiment
• Simple linear regression analysis
• Simple linear regression model
• Model assumptions
• Multiple regression
• Least squares point estimate
• Multiple regression model
• Times series forecasting
• Index numbers
• Forecast error comparisons
• Statistical process control
• Causes of variation
• Control charts
• Nonparametric methods
• Hypothesis test
• Decision theory
• Utility theory
• Posterior probabilities