# chap07 - Statistics for Business and Economics Chapter 7...

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Chap 7-1 Chapter 7 Sampling and Sampling Distributions Statistics for Business and Economics

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Chap 7-2 Chapter Goals After completing this chapter, you should be able to: Describe a simple random sample and why sampling is important Explain the difference between descriptive and inferential statistics Define the concept of a sampling distribution Determine the mean and standard deviation for the sampling distribution of the sample mean, Describe the Central Limit Theorem and its importance Determine the mean and standard deviation for the sampling distribution of the sample proportion, Describe sampling distributions of sample variances p ˆ X
Chap 7-3 Descriptive statistics Collecting, presenting, and describing data Inferential statistics Drawing conclusions and/or making decisions concerning a population based only on sample data Tools of Business Statistics

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Chap 7-4 A Population is the set of all items or individuals of interest Examples: All likely voters in the next election All parts produced today All sales receipts for November A Sample is a subset of the population Examples: 1000 voters selected at random for interview A few parts selected for destructive testing Random receipts selected for audit Populations and Samples
Chap 7-5 Population vs. Sample a b c d ef gh i jk l m n o p q rs t u v w x y z Population Sample b c g i n o r u y

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Chap 7-6 Why Sample? Less time consuming than a census Less costly to administer than a census It is possible to obtain statistical results of a sufficiently high precision based on samples.
Chap 7-7 Simple Random Samples Every object in the population has an equal chance of being selected Objects are selected independently Samples can be obtained from a table of random numbers or computer random number generators A simple random sample is the ideal against which other sample methods are compared

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Chap 7-8 Making statements about a population by examining sample results Sample statistics Population parameters (known) Inference (unknown, but can be estimated from sample evidence) Sample Population Inferential Statistics
Chap 7-9 Inferential Statistics Estimation e.g., Estimate the population mean weight using the sample mean weight Hypothesis Testing e.g., Use sample evidence to test the claim that the population mean weight is 120 pounds Drawing conclusions and/or making decisions concerning a population based on sample results.

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Chap 7-10 Sampling Distributions A sampling distribution is a distribution of all of the possible values of a statistic for a given size sample selected from a population
Chap 7-11 Chapter Outline Sampling Distributions Sampling Distribution of Sample Mean Sampling Distribution of Sample Proportion Sampling Distribution of Sample Variance

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## This note was uploaded on 03/30/2010 for the course STATISTIC Cq498767 taught by Professor Wade during the Spring '10 term at UCSI.

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chap07 - Statistics for Business and Economics Chapter 7...

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