TAILIEUCHUNG - Lecture Business statistics in practice (7/e): Chapter 8 - Bowerman, O'Connell, Murphree

Chapter 8 - Confidence intervals. After mastering the material in this chapter, you will be able to: Calculate and interpret a z-based confidence interval for a population mean when σ is known, describe the properties of the t distribution and use a t table, calculate and interpret a t-based confidence interval for a population mean when σ is unknown,. | Chapter 8 Confidence Intervals Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Confidence Intervals z-Based Confidence Intervals for a Population Mean: σ Known t-Based Confidence Intervals for a Population Mean: σ Unknown Sample Size Determination Confidence Intervals for a Population Proportion Confidence Intervals for Parameters of Finite Populations (Optional) 8- z-Based Confidence Intervals for a Mean: σ Known Confidence interval for a population mean is an interval constructed around the sample mean so we are reasonable sure that it contains the population mean Any confidence interval is based on a confidence level LO8-1: Calculate and interpret a z-based confidence interval for a population mean when σ is known. 8- General Confidence Interval In general, the probability is 1 – α that the population mean μ is contained in the interval The normal point zα/2 gives a right hand tail area under .

• Quản trị kinh doanh
• Business Statistics
• Business statistics in practice
• Descriptive statistics
• Confidence intervals
• Sample size determination
• 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
• 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