TAILIEUCHUNG - Lecture Business statistics in practice (7/e): Chapter 4 - Bowerman, O'Connell, Murphree

Chapter 4 - Probability. After completing this unit, you should be able to: Define a probability and a sample space, list the outcomes in a sample space and use the list to compute probabilities, use elementary probability rules to compute probabilities, compute conditional probabilities and assess independence,. | Chapter 4 Probability Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Probability Probability and Sample Spaces Probability and Events Some Elementary Probability Rules Conditional Probability and Independence Bayes’ Theorem (Optional) Counting Rules (Optional) 4- Probability and Sample Spaces An experiment is any process of observation with an uncertain outcome The possible outcomes for an experiment are called the experimental outcomes Probability is a measure of the chance that an experimental outcome will occur when an experiment is carried out The sample space of an experiment is the set of all possible experimental outcomes The experimental outcomes in the sample space are called sample space outcomes LO4-1: Define a probability and a sample space. 4- Probability If E is an experimental outcome, then P(E) denotes the probability that E will occur and: Conditions 0 P(E) 1 such that: If

• Quản trị kinh doanh
• Business Statistics
• Business statistics in practice
• Descriptive statistics
• Sample spaces
• Elementary probability rules
• Compute conditional probabilities
• 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
• Discrete random variables
• Discrete probability distributions
• Binomial distribution
• 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