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Definition: the act, process, or technique of selecting a representative part of a population for the purpose of determining parameters or characteristics of the whole population.

TYPES OF SAMPLING TECHNIQUES:

Cluster sampling

Cluster sampling is a sampling technique where the entire population is divided into groups, or clusters and a random sample of these clusters are selected. All observations in the selected clusters are included in the sample. Cluster sampling is typically used when the researcher cannot get a complete list of the members of a population they wish to study but can get a complete list of groups or 'clusters' of the population. It is also used when a random sample would produce a list of subjects so widely scattered that surveying them would prove to be far too expensive, for example, people who live in different counties in the Country. Advantages

One advantage of cluster sampling is that it is cheap, quick, and easy. Instead of sampling the entire country when using simple random sampling, the research can instead allocate resources to the few randomly selected clusters when using cluster sampling.

A second advantage to cluster sampling is that the researcher can have a larger sample size than if he or she was using simple random sampling. Because the researcher will only have to take the sample from a number of clusters, he or she can select more subjects since they are more accessible. Disadvantages

One main disadvantage of cluster sampling is that is the least representative of the population out of all the types of probability samples. It is common for individuals within a cluster to have similar characteristics, so when a researcher uses cluster sampling, there is a chance that he or she could have an overrepresented or underrepresented cluster in terms of certain characteristics. This can skew the results of the…...

...Variables Sampling 689 I have edited a portion of Module G from your textbook so that it more closely follows my lecture. I need to acknowledge that this is not my original work and much of it is taken word for word from the 2nd edition of Auditing & Assurance Services by Louwers, Ramsay, Sinason and Strawser. Tad Miller Classical Variables Sampling LEARNING OBJECTIVE Understand the basic process underlying classical variables sampling in an audit examination. When performing substantive procedures, one approach is classical variables sampling. Classical variables sampling methods use normal distribution theory and the Central Limit Theorem to provide a range estimate of the account balance. The auditor uses the sample estimates to determine whether the account balance is fairly stated. The Central Limit Theorem indicates larger sample sizes provide a sampling distribution that more closely reflects a normal distribution. Therefore, larger sample sizes will yield a lower level of sampling risk. In this section, we briefly illustrate mean-per-unit classical variables sampling. We illustrate the manual calculations necessary to determine sample size and evaluate sample results. However, if clients maintain records in electronic format, auditors typically use computer software to perform these tasks. Classical Variables Sampling: Planning In the planning stages of classical variables sampling, the auditor determines the objective of sampling, defines the......

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...EDU 145 Child Development 2 Time Sampling Introduction: Observation is the key to understanding young children and their development. Teachers learn about a child’s physical, social, emotional, cognitive and language domains as they watch children in multiple learning experiences. Through your observations you will learn to identify appropriate observation techniques (competency # 4). Observation also allows you to meet the CPCC core competencies of communication, critical thinking and information technology and quantitative literacy. Outcome Assessment Standards: NAEYC Standards Standard 1: Promoting Child Development Standard 3: Observing, Documenting and Assessing to Support Young Children & Families. Support Skill 3: Written & Verbal Skills CPCC Core Competencies Communication, Critical Thinking, Information Technology & Quantitative Literacy Description of Specific Assignment Requirements Adapted from Observing Development of Young Children (Beaty, 1990)) In the time sampling method, the observer records the frequency of a behavior’s occurrence over time. The behavior must be overt and frequent (at least once every fifteen minutes) to be a candidate for sampling. For example, talking, hitting, and crying are such behaviors, because they can be clearly seen and counted. Time sampling thus involves observing specified behavior of an individual and recording the presence or absence of this......

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...Sampling Techniques Psychology 341 August 11, 2013 ABSTRACT The present research paper was designed to discuss the different types of sampling methods used to conduct research in the field of Psychology. The sampling techniques included in this paper are probability sampling, non probability sampling, surveys and questionnaires. The use of examples for each type of technique is given to further the understanding of each specific type. Furthermore, some the most important aspects that should considered before selecting a method are outlined in detail. Sampling Techniques When conducting research, it is almost impossible to study the entire population that we are interested in looking at more in depth. For example, if we were interested in comparing the level of romantic satisfaction among college students in the United States, it would be practically impossible to survey every single person who is attending college in the country. Not only would it take an extremely long time to do so, but it would also be very expensive. That is why researchers will use small samples from the population to gather their data instead. A sample is particularly useful because it allows the researcher to make inferences about a specific population without having to actually survey the entire population (Trochim, 2006). There are several sampling techniques used to gather information about a sample. Some of these include probability sampling, non probability sampling, surveys, and......

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...Sampling Designs • 1. Simple random sampling (SRS) Steps: – (1) Assign a single number to each element in the sampling frame. – (2) Use random numbers to select elements into the sample until the desired number of cases is obtained. • The method is not very different from winning a lottery. 2. Systematic Sampling • Steps: – (1) Calculate the sampling interval as the ratio between population size and sample size, I = N/n. – (2) Arrange all elements in the population in an order. – (3) Select a case in the first interval randomly. – (4) Select every ith case from this point. 2. Systematic Sampling (continued) I I 1st element, randomly chosen I I I I – Systematic Sampling is easier and simpler than SRS – The text warns of a danger to this method. What is it? 3. Stratified Sampling • Stratified sampling is more complicated than SRS. The advantage is the guaranteed representativeness in some important characteristics. • For example, say that we want to select a sample of 100 individuals. Sex ratio in the sample is up to chance if we do SRS. We can guarantee the 50-50 split if we do stratified sampling: Stratified Sampling, Graphic Representation Population SRS SRS Sample • Stratified sampling is often used to reduce the variability of a sample. Oversampling, Graphic Representation Population SRS SRS Sample • Increasing the representation of a group in a sample. This is often done when groups are very different in......

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...Sampling techniques: Advantages and disadvantages Technique | Descriptions | Advantages | Disadvantages | Simple random | Random sample from whole population | Highly representative if all subjects participate; the ideal | Not possible without complete list of population members; potentially uneconomical to achieve; can be disruptive to isolate members from a group; time-scale may be too long, data/sample could change | Stratified random | Random sample from identifiable groups (strata), subgroups, etc. | Can ensure that specific groups are represented, even proportionally, in the sample(s) (e.g., by gender), by selecting individuals from strata list | More complex, requires greater effort than simple random; strata must be carefully defined | Cluster | Random samples of successive clusters of subjects (e.g., by institution) until small groups are chosen as units | Possible to select randomly when no single list of population members exists, but local lists do; data collected on groups may avoid introduction of confounding by isolating members | Clusters in a level must be equivalent and some natural ones are not for essential characteristics (e.g., geographic: numbers equal, but unemployment rates differ) | Stage | Combination of cluster (randomly selecting clusters) and random or stratified random sampling of individuals | Can make up probability sample by random at stages and within groups; possible to select random sample when population lists are very localized...

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...CHAPTER 9 Audit Sampling Review Questions 9-1 Nonstatistical sampling is an audit sampling technique in which the risk of sampling error is estimated by the auditors using professional judgment rather than by the laws of probability. Statistical sampling involves the quantification of the risk of sampling error through the use of mathematics and laws of probability. 9-2 Sampling risk is the possibility that the auditors will make an erroneous decision based on a sample result. To control sampling risk the auditors increase the size of their samples. Nonsampling risk is the risk of erroneous conclusions by the auditors based on any factor other then sampling. For example, the auditors may perform inappropriate tests, or they may not recognize errors in the sample items examined. Nonsampling risk may be controlled by adequate planning and supervision of engagements, and the establishment of effective quality control policies and procedures. 9-3 The physical representation of the actual population is the recorded value that represents the population. For example, if the auditors use a computer printout of recorded accounts payable from which to sample, they must attempt to determine that it properly includes all accounts payable. 9-4 All three of the methods of selecting items for examination (random number table selection, systematic selection, random number generator selection) will produce a random sample if properly applied. ......

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...Sampling Douglas P. Shumski April 27, 2014 MATH301-1402A-01 Susan Lee 1. In your own words, discuss the differences between discrete and continuous random variables because the statistical analysis of each type of variable is different. Discrete Variable – This type of variable is only in the form of a particular value, and does not consider any values that may fall in between each particular value. The example that I would provide here would be that I have two children. I do not have 2.8 children. Continuous Random Variable - This type of variable can take on any value that is available on a range. My example of this type of variable would be the measure of temperature. The temperature can be measured in tenths, such as 86.9 degrees, and not the whole number of 87 degrees. A person’s individual height or weight could also be considered as a continuous random variable. 2. Roll a die 20 times and record the event in Excel |Roll 1 |1 |Roll 11 |6 | |Roll 2 |5 |Roll 12 |5 | |Roll 3 |3 |Roll 13 |2 | |Roll 4 |6 |Roll 14 |4 | |Roll 5 |6 |Roll 15 |6 | |Roll 6 |3 |Roll 16 |3 | |Roll 7 |5 |Roll 17 |4 | |Roll 8 |4 |Roll 18 |6 | |Roll 9 |2 |Roll 19 |5 | |Roll 10 |1 ...

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...Explain each sampling technique discussed in the “Visual Learner: Statistics” in your own words, and give examples of when each technique would be appropriate. Statistical Hypotheses: There are two types of statistical hypotheses to include null and alternative hypothesis. Null Hypothesis - Samples observations resulting purely by chance. Alternative Hypothesis - Sample observations influenced by non-random causes. In example, when determining the end result in a coin flip. A null hypothesis may result in half Heads and half in Tails. However, the alternative hypothesis may reflect differently with the number of Heads and the number of Tails received. In conclusion, if the number of flips totaled 100 times, resulting in 60 Heads and 40 Tails, we would determine the null hypothesis would be rejected and not of use. The coin would be deemed as not fair nor balanced. Blocking - Is the act of grouping experimental units into block segments with comparable characteristics that may influence the end result of the experiment. The design with both control and randomization, are taken into consideration (Easton, Valerie J 2014). In example, a study being carried out has a total of 100 subjects. The plan is to divide the subjects into random, yet equally split groups of four. Census - Is data collected from every individual within a population and calculated to assist with achieving statistical information. An example of a census is the United States Census. It...

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...Sampling Sampling Third Edition STEVEN K. THOMPSON Simon Fraser University A JOHN WILEY & SONS, INC., PUBLICATION Copyright © 2012 by John Wiley & Sons, Inc. All rights reserved. Published by John Wiley & Sons, Inc., Hoboken, New Jersey. Published simultaneously in Canada. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 750-4470, or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011, fax (201) 748-6008, or online at http://www.wiley.com/go/permission. Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and speciﬁcally disclaim any implied warranties of merchantability or ﬁtness for a particular purpose. No warranty may be created or extended by sales representatives......

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...Logic of Sampling Name Institution The sampling of a given data especially population is very important in analysing information. This depends on the method used to sample a given set of data. The methods include random sampling, stratified sampling, and systematic sampling. Every sampling method uses logic in sampling of data. This involves the procedure in sampling of a given set of information. Random sampling The random numbers used from the random tables include 11168, 36318, 75064, 21215, 91791, 76831, 10468, 44482, 66558, and 12032. The data in the table provide is labelled in terms of two digits. 11168- 01, 11, 64 36318- 03, 63, 18 75064- 07, 50, 64 21215- 02, 12, 15 91791- 09, 17, 91 76831- 07, 68, 31 10468- 01, 04, 68 44482- 04, 44, 82 66538- 06, 65, 38 12032- 01, 20, 32 The first ten numbers from the random table within the boundaries of the data are selected. This does not include the repeating entry. The selected random numbers are from the list of random table numbers include 01, 11, 64, 03, 63, 18, 07, 50, 02, and 12. Names of the selected ten random numbers 1. Lauren Aaronson 2. Andrew Abbot 3. James Abbot 4. Saleha Abedin 5. Christopher Abells 6. Marjorie Abend-Wein 7. Jill Abood 8. Reed Adams 9. Evan Adelson 10. Francis Adeola Procedure in random sampling The procedure in random sampling uses random tables to determine the values to sample. Before selecting the values, each value of the data......

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...org/OurWork/Schools/Fieldwork+and+local+learning/Fieldwork+techniques/Sampling+techniques.htm Two categories of sampling techniques, and variety of sampling techniques within each category Sampling techniques What is sampling? • A shortcut method for investigating a whole population • Data is gathered on a small part of the whole parent population or sampling frame, and used to inform what the whole picture is like Why sample? In reality there is simply not enough; time, energy, money, labour/man power, equipment, access to suitable sites to measure every single item or site within the parent population or whole sampling frame. Therefore an appropriate sampling strategy is adopted to obtain a representative, and statistically valid sample of the whole. Sampling considerations • Larger sample sizes are more accurate representations of the whole • The sample size chosen is a balance between obtaining a statistically valid representation, and the time, energy, money, labour, equipment and access available • A sampling strategy made with the minimum of bias is the most statistically valid • Most approaches assume that the parent population has a normal distribution where most items or individuals clustered close to the mean, with few extremes • A 95% probability or confidence level is usually assumed, for example 95% of items or individuals will be within plus or minus two standard deviations from the mean • This also means that up to five per cent may lie......

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...Summary Audit sampling is necessary and helps improve an audit engagement because examining all items are rather very timely, requires more effort, and of course, at higher cost. Audit risks such as inherent, control and detection risk are first assessed when doing audit sampling. Low control risk means auditors rely extensively on the entity's internal control, and vice versa. The process for determining risks and gathering evidences to provide reasonable assurance are done through other audit procedures such as tests of controls and tests of details. These procedures are done by sampling. Using sampling, when auditors do not obtain sufficient and appropriate evidences, there is a risk of not identifying material errors and therefore result in a wrong conclusion. The use of either non-statistical sampling techniques or statistical ones does not directly affect application of audit procedures, appropriateness of audit evidences or courses of actions that could be taken. Even though the procedures in non-statistical sampling is less formal, they are still rigorous. Non-statistical sampling method involves eight steps namely establish objective test, defining the population, determining distortions, determining the appropriate sample size, determination of the right method for the sample selection, proper testing of the selected sample, extrapolating results, risk assessment. Firms include in their policies the techniques which they use to implement auditing procedures....

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...merits of alternative sampling frames. Suggest most appropriate one and justify your selection. Research population is the target population on which a study or research is conducted through various different methods inorder to reach a conclusion from the data generated. It is for the benefit of the population directly or indirectly. But, due to very large size of research population, it is not feasible to test all the individuals of the population since it will take too much time and will be expensive as well. So the researchers take few individuals from the research population ( a subset of the set of target population) using sampling techniques. These techniques helps to take out sample as per the requirements of the type of research that is to be conducted. A research population is also known as a well-defined collection of individuals or objects known to have similar characteristics. All individuals or objects within a certain population usually have a common, binding characteristic or trait. Usually, the description of the population and the common binding characteristic of its members are the same. "Government officials" is a well-defined group of individuals which can be considered as a population and all the members of this population are indeed officials of the government. There are various sources from which a sample is created. A set of all these sources is called a Sampling frame from which the sample is selected. With the help of sampling frames,......

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...Unit 3 – Sampling Teri Isbell American InterContinental University Abstract Three different types of surveys will be discussed for sample size and how they compare to each other. A personal survey’s information is provided and the breakdown of the answers is shown in charts for review. A personal opinion regarding how survey information can be used with a business or other service is discussed. Introduction An entertainment, political, and general survey will be examined for sample size and discussed in this paper. A personal survey will also be reviewed and additional information will be discussed as to how they relate to each other and how the information could be used in a business or other setting. Part 1: Survey Analysis: Entertainment Social gaming is taking the desktop and console gaming world to new heights by attracting gamers that might not have every touched a video game before according to Shaer, (2010). He reports that 56.8 million American consumers over the age of 6 had participated in social game playing over the past three months. According to the U.S. Census Bureau, the 2010 population was 281,421,906, and Shaer’s 56.8 million consumers represent approximately 20% of the overall population. I was surprised to find the accuracy in Shaer’s numbers representing one-fifth of the U.S. population in 2010. That is a staggering number of people doing nothing more than playing games! To further understand the impact these numbers have on social......

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...SAMPLING: In statistics and survey methodology, sampling is concerned with the selection of a subset of individuals from within a population to estimate characteristics of the whole population. The three main advantages of sampling are that the cost is lower, data collection is faster, and since the data set is smaller it is possible to ensure homogeneity and to improve the accuracy and quality of the data. The sampling process comprises several stages: * Defining the population of concern * Specifying a sampling frame, a set of items or events possible to measure * Specifying a sampling method for selecting items or events from the frame * Determining the sample size * Implementing the sampling plan * Sampling and data collecting PROBABILITY AND NON-PROBABILITY SAMPLING: A probability sampling scheme is one in which every unit in the population has a chance (greater than zero) of being selected in the sample, and this probability can be accurately determined. The combination of these traits makes it possible to produce unbiased estimates of population totals, by weighting sampled units according to their probability of selection. Non-probability sampling is any sampling method where some elements of the population have no chance of selection (these are sometimes referred to as 'out of coverage'/'under covered'), or where the probability of selection can't be accurately determined. It involves the selection of elements based on assumptions......

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