TAILIEUCHUNG - Lecture Business statistics in practice (7/e): Chapter 12 - Bowerman, O'Connell, Murphree

Chapter 12 - Experimental design and analysis of variance. After mastering the material in this chapter, you will be able to: Explain the basic terminology and concepts of experimental design, compare several different population means by using a one-way analysis of variance, compare treatment effects and block effects by using a randomized block design. | Experimental Design and Analysis of Variance Chapter 12 Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Experimental Design and Analysis of Variance Basic Concepts of Experimental Design One-Way Analysis of Variance The Randomized Block Design Two-Way Analysis of Variance 12- Basic Concepts of Experimental Design Up until now, we have considered only two ways of collecting and comparing data: Using independent random samples Using paired (or matched) samples Often data is collected as the result of an experiment To systematically study how one or more factors (variables) influence the variable that is being studied LO12-1: Explain the basic terminology and concepts of experimental design. 12- Experimental Design #2 In an experiment, there is strict control over the factors contributing to the experiment The values or levels of the factors are called treatments For example, in testing a medical .

• Quản trị kinh doanh
• Business Statistics
• Business statistics in practice
• Descriptive statistics
• Experimental design
• Analysis of variance
• Randomized block design
• 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
• 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
• 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