1 1 Slide © 2016 Cengage Learning. All Rights Reserved. A population is the set of all the elements of interest. A population is the set of all the elements.

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1 1 Slide © 2016 Cengage Learning. All Rights Reserved. A population is the set of all the elements of interest. A population is the set of all the elements of interest. A sample is a subset of the population. A sample is a subset of the population. An element is the entity on which data are collected. An element is the entity on which data are collected. The reason we select a sample is to collect data to The reason we select a sample is to collect data to answer a research question about a population. answer a research question about a population. The reason we select a sample is to collect data to The reason we select a sample is to collect data to answer a research question about a population. answer a research question about a population. A frame is a list of the elements that the sample will A frame is a list of the elements that the sample will be selected from. be selected from. A frame is a list of the elements that the sample will A frame is a list of the elements that the sample will be selected from. be selected from. Chapter 7 - Sampling

2 2 Slide © 2016 Cengage Learning. All Rights Reserved. The sample results provide only estimates of the The sample results provide only estimates of the values of the population characteristics. values of the population characteristics. The sample results provide only estimates of the The sample results provide only estimates of the values of the population characteristics. values of the population characteristics. With proper sampling methods, the sample results With proper sampling methods, the sample results can provide “good” estimates of the population can provide “good” estimates of the population characteristics. characteristics. With proper sampling methods, the sample results With proper sampling methods, the sample results can provide “good” estimates of the population can provide “good” estimates of the population characteristics. characteristics. Introduction The reason is simply that the sample contains only a The reason is simply that the sample contains only a portion of the population. portion of the population. The reason is simply that the sample contains only a The reason is simply that the sample contains only a portion of the population. portion of the population. This chapter provides the basis for determining how This chapter provides the basis for determining how large the estimation error might be. large the estimation error might be. This chapter provides the basis for determining how This chapter provides the basis for determining how large the estimation error might be. large the estimation error might be.

3 3 Slide © 2016 Cengage Learning. All Rights Reserved. In large sampling projects, computer-generated random numbers are often used to automate the sample selection process. In large sampling projects, computer-generated random numbers are often used to automate the sample selection process. Sampling without replacement is the procedure used most often. Sampling without replacement is the procedure used most often. Replacing each sampled element before selecting subsequent elements is called sampling with replacement. Replacing each sampled element before selecting subsequent elements is called sampling with replacement. Sampling from a Finite Population n Finite populations are often defined by lists such as: Organization membership roster Organization membership roster Credit card account numbers Credit card account numbers Inventory product numbers Inventory product numbers n A simple random sample of size n from a finite population of size N is a sample selected such that each possible sample of size n has the same probability of being selected.

4 4 Slide © 2016 Cengage Learning. All Rights Reserved. The random numbers generated by Excel’s RAND function follow a uniform probability distribution between 0 and 1. Step 1: Assign a random number to each of the 900 applicants. applicants. Step 2: Select the 30 applicants corresponding to the 30 smallest random numbers. 30 smallest random numbers. Sampling from a Finite Population Using Excel n Example: St. Andrew’s College St. Andrew’s College received 900 applications for admission in the upcoming year from prospective students. The applicants were numbered, from 1 to 900, as their applications arrived. The Director of Admissions would like to select a simple random sample of 30 applicants. St. Andrew’s College received 900 applications for admission in the upcoming year from prospective students. The applicants were numbered, from 1 to 900, as their applications arrived. The Director of Admissions would like to select a simple random sample of 30 applicants.

5 5 Slide © 2016 Cengage Learning. All Rights Reserved. n Excel Value Worksheet n Use Rand to assign random number to obervation Note: Rows are not shown. Sampling from a Finite Population Using Excel AB 1 Applicant Number Random Number AB 1 Applicant Number 21=RAND() Random Number

6 6 Slide © 2016 Cengage Learning. All Rights Reserved. n Put Random Numbers in Ascending Order n Set calculation option to manual Step 4 Choose Sort Smallest to Largest Step 3 In the Editing group, click Sort & Filter Step 2 Click the Home tab on the Ribbon Step 1 Select any cell in the range B2:B901 Sampling from a Finite Population Using Excel AB 1 Applicant Number Random Number

7 7 Slide © 2016 Cengage Learning. All Rights Reserved. n Populations are often defined by an ongoing process whereby the elements of the population consist of items generated as though the process would operate indefinitely. Sampling from a Process Some examples of on-going processes, with infinite Some examples of on-going processes, with infinite populations, are: populations, are: parts being manufactured on a production line parts being manufactured on a production line transactions occurring at a bank transactions occurring at a bank telephone calls arriving at a technical help desk telephone calls arriving at a technical help desk customers entering a store customers entering a store

8 8 Slide © 2016 Cengage Learning. All Rights Reserved. Sampling from a Process The sampled population is such that a frame cannot The sampled population is such that a frame cannot be constructed. be constructed. In the case of infinite populations, it is impossible to In the case of infinite populations, it is impossible to obtain a list of all elements in the population. obtain a list of all elements in the population. The random number selection procedure cannot be The random number selection procedure cannot be used for infinite populations. used for infinite populations. n A random sample from an infinite population is a sample selected such that the following conditions sample selected such that the following conditions are satisfied. are satisfied. Each of the sampled elements is independent. Each of the sampled elements is independent. Each of the sampled elements follows the same probability distribution as the elements in the population. Each of the sampled elements follows the same probability distribution as the elements in the population.