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

Chapter 7 - Sampling and sampling distributions. This chapter includes contents: Random sampling; the sampling distribution of the sample mean; the sampling distribution of the sample proportion; stratified random, cluster, and systematic sampling (optional); more about surveys and errors in survey sampling (optional); deviation of the mean and variance of the sample mean (optional). | Chapter 7 Sampling and Sampling Distributions Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Sampling and Sampling Distributions Random Sampling The Sampling Distribution of the Sample Mean The Sampling Distribution of the Sample Proportion Stratified Random, Cluster, and Systematic Sampling (Optional) More about Surveys and Errors in Survey Sampling (Optional) Deviation of the Mean and Variance of the Sample Mean (Optional) 7- Random Sampling If we select n elements from a population in such a way that every set of n elements in the population has the same chance of being selected, the then elements we select are said to be a random sample In order to select a random sample of n elements from a population, we make n random selections from the population On each random selection, we give every element remaining in the population for that selection the same chance of being chosen LO7-1: Explain the . | Chapter 7 Sampling and Sampling Distributions Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Sampling and Sampling Distributions Random Sampling The Sampling Distribution of the Sample Mean The Sampling Distribution of the Sample Proportion Stratified Random, Cluster, and Systematic Sampling (Optional) More about Surveys and Errors in Survey Sampling (Optional) Deviation of the Mean and Variance of the Sample Mean (Optional) 7- Random Sampling If we select n elements from a population in such a way that every set of n elements in the population has the same chance of being selected, the then elements we select are said to be a random sample In order to select a random sample of n elements from a population, we make n random selections from the population On each random selection, we give every element remaining in the population for that selection the same chance of being chosen LO7-1: Explain the concept of random sampling and select a random sample. 7- With or Without Replacement We can sample with or without replacement With replacement, we place the element chosen on any particular selection back into the population We give this element a chance to be chosen on any succeeding selection Without replacement, we do not place the element chosen on a particular selection back into the population We do not give this element a chance to be chosen on any succeeding selection It is best to sample without replacement LO7-1 7- Sampling Distribution of the Sample Mean The sampling distribution of the sample mean x is the probability distribution of the population of the sample means obtainable from all possible samples of size n from a population of size N LO7-2: Describe and use the sampling distribution of the sample mean. 7- General Conclusions If the population of individual items is normal, then the population of all sample means is also normal Even if the .

• Quản trị kinh doanh
• Business Statistics
• Business statistics in practice
• Descriptive statistics
• Sampling distributions
• Random sampling
• Stratified random
• 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
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• Interval estimation
• Hypothesis tests
• Simple linear regression
• Basic statistics
• Statistics for business
• Describing data
• Types of statistics
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• Statistical inference
• Illustrate sampling
• Graphical methods
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• Graphically summarizing qualitative data
• Numerical methods
• Describing central tendency
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• Elementary probability rules
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• Uniform distribution
• Confidence intervals
• Sample size determination
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