TAILIEUCHUNG - Lecture Business statistics in practice (7/e): Chapter 15 - Bowerman, O'Connell, Murphree

Chapter 15 - Multiple regression and model building. After mastering the material in this chapter, you will be able to: Explain the multiple regression model and the related least squares point estimates, explain the assumptions behind multiple regression and calculate the standard error, calculate and interpret the multiple and adjusted multiple coefficients of determination,. | Multiple Regression and Model Building Chapter 15 Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Multiple Regression and Model Building The Multiple Regression Model and the Least Squares Point Estimate Model Assumptions and the Standard Error R2 and Adjusted R2 (This section can be read anytime after reading Section ) The Overall F Test Testing the Significance of an Independent Variable Confidence and Prediction Intervals 15- Multiple Regression and Model Building Continued The Sales Territory Performance Case Using Dummy Variables to Model Qualitative Independent Variables Using Squared and Interaction Variances Model Building and the Effects of Multicollinearity Residual Analysis in Multiple Regression Logistic Regression 15- The Multiple Regression Model and the Least Squares Point Estimate Simple linear regression used one independent variable .

• Quản trị kinh doanh
• Business Statistics
• Business statistics in practice
• Descriptive statistics
• Multiple regression
• Least squares point estimate
• Multiple regression model
• 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
• 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
• 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