...Simple Random Sampling is done when every individual subject in the population has an equal chance of being selected for the sample, without any bias (Explorable). For example, if a researcher wants to represent the population as a whole, they can pick random numbers or names out a hat or use a program to randomly choose names so the information is not biased. Stratified Sampling is performed by, dividing the population into at least two (or more) groups or sections, which share certain characteristics, called “strata” (Explorable). For example, a researcher who wants to compare the average economic status of different racial groups may use this technique in order to divide the population into groups based on race and ethnicities and then compare the whole average from each ethnic group. Cluster Sampling is done by dividing the population into separate sections or “clusters” and then picks a cluster randomly and chooses all the members from those clusters for the sample (Explorable). For example, using a geographical cluster, in order to look at the academic performance of students. The researcher can divide Nassau County in Long Island into clusters based on the towns. Then, randomly select a certain number of these clusters or towns and include all the students from those clusters to be part of the sample. Systematic Sampling is performed by, using and selecting a point at which to begin and then selecting every x number after that point (Explorable). For example,...
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...2011 Chapter 7 - Sampling and Sampling Distributions Practice Exam - Solution Instructors: Dr. Samir Safi Mr. Ibrahim Abed SECTION I: MULTIPLE-CHOICE 1. Sampling distributions describe the distribution of a) parameters. b) statistics. c) both parameters and statistics. d) neither parameters nor statistics. 2. The Central Limit Theorem is important in statistics because a) for a large n, it says the population is approximately normal. b) for any population, it says the sampling distribution of the sample mean is approximately normal, regardless of the sample size. c) for a large n, it says the sampling distribution of the sample mean is approximately normal, regardless of the shape of the population. d) for any sized sample, it says the sampling distribution of the sample mean is approximately normal. 3. Which of the following statements about the sampling distribution of the sample mean is incorrect? a) The sampling distribution of the sample mean is approximately normal whenever the sample size is sufficiently large ( n ≥ 30 ). b) The sampling distribution of the sample mean is generated by repeatedly taking samples of size n and computing the sample means. c) The mean of the sampling distribution of the sample mean is equal to µ . d) The standard deviation of the sampling distribution of the sample mean is equal to σ . 4. Which of the following is true about the sampling distribution of the sample mean? a) The mean of the sampling distribution is...
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...and not always be completely related to the needs of a specific project. Qualitative research: Subjective research where the researcher will ask a customer for their opinion or thoughts. Quantitative research: Research that uses a large sample of people to gather statistical information. Sampling: Sampling is concerned with the selection of a subset of individuals from within a statistical population to estimate characteristics of the whole population. In business and medical research, sampling is widely used for gathering information about a population. Random sampling: In this technique, each member of the population has an equal chance of being selected as subject. The entire process of sampling is done in a single step with each subject selected independently of the other members of the population. Quota sampling: In quota sampling, a population is first segmented into mutually exclusive sub-groups. Then judgment is used to select the subjects or units from each segment based on a specified proportion. Quota sampling is useful when time is limited, a sampling frame is not available, the research budget is very tight or when detailed accuracy is not important. Stratified sampling: Stratification is the process of dividing members of the...
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...uminary ReviResearch Definitions and Study Guide for Luminary Comps HC3 - 2013 Ideology | Oversimplified explanations for social behavior that focus on one or a few variables to explain a social phenomenon. Ideologies are resistant to change and become entwined with moral, instead of empirical arguments. Begins and ends with facts. | Social Theory | A systematic, detailed means of explaining why a social phenomenon exists that recognizes the influences of a multitude of factors, is subject to change, and avoids moral arguments in favor of empirical arguments. Begins with a question and ends with facts. | Concepts or Constructs | Abstract terms people use to describe reality. People may share general definitions or understandings of a concept, but because they are abstract, the specific interpretation of these concepts among many people may differ. An abstraction. Cannot be measured directly. | Dimensions | A theoretical term used to describe clusters of concepts that together represent a broader, more complex concept. | Conceptual Definition | Is the working or “dictionary type” definition a researcher uses for a concept. It tends to be nonspecific | Operational Definition | Is used to define something (e.g. a variable, term, or object) in terms of a process (or set of validation tests) needed to determine its existence, duration, and quantity. | Measurement | The process of observing concepts, as indicated by their operational definitions, and assigning some...
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...BSHS/435 Sampling A sample is drawn from a population, which refers to all possible cases of what the researcher is interested in studying. A sample consists of one or two elements selected from a population. To select a good sample we have to clearly define the population from which we will be drawing a sample. Failure to do so can result in inaccurate conclusions. In probability sampling each element has an equal chance of inclusion. The simplest technique for probability samples is Simple Random Sampling. Simple random sampling treats the target population as a unitary whole. We might start off with a sampling frame which has a list of the whole population—or as much information as we can obtain. Next we would number the elements in the sampling frame sequentially and select elements from the list randomly. We would not know what the outcome would be, but each has an equal shot at being chosen. We can also program the computer to choose a random sample. Researchers may also use non probability sampling. In this type of sampling the researcher does not know the probability of each population’s elements inclusion in the sample (Dejong, 2011). Data Collection There are many different ways to collect data for research. Measures differ from one another in terms called levels of measurement. Nominal measures classify observations into mutually exclusive and exhaustive categories. They represent nominal variables such as sex, ethnicity, religion...
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...Facilitators/Tutors and Tutorials Summary . . . . INTRODUCTION Data collection methodology is a two credit unit first semester course available to first semester course available to students of Bachelor of Education (B.Ed) Library and Information science. 4 Research involves data collection, any discipline of the social sciences, education and even the sciences needs a sound knowledge of research; how to conduct research, ethics of research and generally to write a report or design a study. The use and importance of research cannot be overemphasized. All students undergoing any form of degree programme is required to write a project, thesis or dissertation. This course offers a complete guide to such write ups including statistical techniques in sampling measurements and ethics of research. What you will learn in this course The course consist of units and a course guide which informs you briefly...
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...Non-Probability Sampling Non-probability sampling is a sampling technique where the samples are gathered in a process that does not give all the individuals in the population equal chances of being selected. In any form of research, true random sampling is always difficult to achieve. Most researchers are bounded by time, money and workforce and because of these limitations, it is almost impossible to randomly sample the entire population and it is often necessary to employ another sampling technique, the non-probability sampling technique. In contrast with probability sampling, non-probability sample is not a product of a randomized selection processes. Subjects in a non-probability sample are usually selected on the basis of their accessibility or by the purposive personal judgment of the researcher. The downside of the non-probablity sampling method is that an unknown proportion of the entire population was not sampled. This entails that the sample may or may not represent the entire population accurately. Therefore, the results of the research cannot be used in generalizations pertaining to the entire population. Types of Non-Probability Sampling Convenience Sampling Convenience sampling is probably the most common of all sampling techniques. With convenience sampling, the samples are selected because they are accessible to the researcher. Subjects are chosen simply because they are easy to recruit. This technique is considered easiest, cheapest and least time...
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...QNT 561 Week 3 Sample Size and Data Collection Click Link Below To Buy: http://hwaid.com/shop/qnt-561-week-3-sample-size-and-data-collection/ QNT 561 Week 3 Sample Size and Data Collection Sampling and Data Collection Plan – Assessment Activity – Week3 – QNT/561 – eCampus Part 1: Sampling Design Write a 350- to 700-word paper using the scenario and two variables your learning team developed for the Week 2 Business Research Project Part 1 assignment, in which the goal is to submit a random sampling plan in such detail that another researcher could replicate the method. Discuss the following: • Population and size • The target population and brief reasoning • Sampling element which may be conducted through any of the following: o Data mining o Survey (If a survey is chosen, create a 5-10 question document), or o Observation • The sample size • Method of random sampling which may include: o Simple o Stratified o Systematic o Cluster Calculate the sample size for the mean or sample or sample size for the proportion, using a 95% confidence level, estimated population standard deviation or estimate of the true population proportion, and a 5% margin of error. Place the calculation in the Appendix. Discuss how validity and reliability will be achieved. If applicable, explain how human subjects will be protected. Part 2: Data Collection Explain how the data will be physically collected. Explain where data will be stored and how it will be protected...
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...processed January 1, 2007 through December 31, 2007 AUDIT OBJECTIVES: • To determine internal control compliance to sub objectives for payroll and personnel cycle, sales/revenue and collection cycle, and the acquisition and payment cycle. • To obtain control evidence and documentation about the existence, accuracy, classification, timing and completeness of recorded acquisition transactions. CRITERIA: Statement on Auditing Standards (SAS) No. 99 – Fraud Auditing Standards AUDITOR ASSIGNMENTS: John Butler – Sales and Collection David Sargent – Payroll and Personnel Perry Boydstun – Acquisition and Payment Cycle METHODOLOGY: Each auditor will perform their assigned area of tests of controls and substantive test using sampling techniques as appropriate. Strengths and weaknesses’ should be denoted by using a “S” or “W” on each area applicable area of the flowchart and checklist of each assigned area. The summary status (“Ss” and “Ws”) will be listed in the bridge worksheet for SOX 404 Audit analysis. Bridge Worksheet for Sales and Collection Cycle – SOX 404 Audit Public companies typically rely heavily on proper internal controls to maintain an effective sales and collection cycle. As such, AOW will need to expand the substantive tests of transactions to include tests on controls. First of all, it is vital for AOW to understand the sales and collection cycle and typical account balances within Apollo Shoes. Second, it is vital to understand the documentation...
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...critical behavior in research analysis will analyze an ethical issue raised in the article, The Causal Generalization Paradox: The Case of Treatment Outcome Research, written by Graham L. Staines. The article by Staines discusses the causal generalization paradox. The ethical issue at the heart of the article is the use of improper sampling procedures. With the vast amount of research taking place and random assignment techniques, less of a priority is being placed upon random sampling. According to Staines,2008 experimental research typically selects units, in part or in whole, at the convenience of the researcher. The researcher then makes no attempt, or often times only a limited attempt, to ensure that this sample is an accurate representation of some larger group or population. This form of convenience sampling is an ethical issue simply because experimental data based upon the use of “convenience samples rather than probability based samples, there is almost never a formal justification, or set of rigorous guidelines, for generalizing the study’s findings to other populations” (Staines, 2008). The generalization paradox and improper sampling procedures may often cause...
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...questionnaires. PROCEDURE After done and printing out the questionnaires, we the researchers started to distribute the questionnaires randomly using a random sampling method which is a coin toss method at University Tunku Abdul Rahman Perak Campus. We explained the objective of this research to the participants and obtained informed consent from participants after the participants agreed to participate in this research. Participants were given 10-15 minutes to complete the questionnaires. Researchers collected back the questionnaires right after participants completed it. Participants are not allowed to change any of the answers after the submission of questionnaire. The process of this data collection took 2 days. It started from 17th January 2014 to 18th January 2014. HOW TO GET SAMPLE The population of this research is UTAR, Perak Campus students. While our sample is 50 undergraduate students from Faculty of Arts and Social (FAS). These 50 students were divided into 2 groups according to gender which is male and female. Therefore, our sample was 25 male students and 25 female students from FAS. We got this sampling method through random sampling method. Random sampling means every member of the population have an equal chance of being selected. Our sample is said to be an unbiased sample because the sample is chosen at random from the population. We used ‘coin toss’ method to randomly select our sample. The results are based on the coin side produced upon tossed. If the result...
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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 or...
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...Chapter 1: The Role of BR I. The Nature of Research A. BR defined B. Applied & basic BR C. The scientific method II. Managerial Value of BR A. Identifying problems or opportunities B. Diagnosing & assessing problems or opportunities C. Selecting & implementing a course of action D. Evaluating the course of action III. When is BR Needed? A. Time constraints B. Availability of data C. Nature of the decision D. Benefits vs costs IV. BR In The 21st Century A. Communication technologies B. Global BR Chapter 3: Theory Building I. Introduction A. What is a theory? B. What are the goals of theory? II. Research Concepts, Constructs, Proposition, Variables & Hypotheses A. Research concepts & constructs B. Research proposition & hypotheses III. Understanding Theory A. Verifying theory B. Theory building Chapter 5: The Human Side of BR: Organizational & Ethical Issue I. Introduction II. Ethical issue in BR A. Ethical qs are philosophical qs B. General rights & obligation of concerned parties C. Rights & obligation of the research participant * The obligation to be truthful * Participants’ right to privacy * Active & Passive research * Deception in research designs & the right to be informed * Experiment designs * Descriptive research * Protection from harm D. Rights & obligation of the...
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...2011 Chapter 7 - Sampling and Sampling Distributions Practice Exam - Solution Instructors: Dr. Samir Safi Mr. Ibrahim Abed SECTION I: MULTIPLE-CHOICE 1. Sampling distributions describe the distribution of a) parameters. b) statistics. c) both parameters and statistics. d) neither parameters nor statistics. 2. The Central Limit Theorem is important in statistics because a) for a large n, it says the population is approximately normal. b) for any population, it says the sampling distribution of the sample mean is approximately normal, regardless of the sample size. c) for a large n, it says the sampling distribution of the sample mean is approximately normal, regardless of the shape of the population. d) for any sized sample, it says the sampling distribution of the sample mean is approximately normal. 3. Which of the following statements about the sampling distribution of the sample mean is incorrect? a) The sampling distribution of the sample mean is approximately normal whenever the sample size is sufficiently large ( n ≥ 30 ). b) The sampling distribution of the sample mean is generated by repeatedly taking samples of size n and computing the sample means. c) The mean of the sampling distribution of the sample mean is equal to µ . d) The standard deviation of the sampling distribution of the sample mean is equal to σ . 4. Which of the following is true about the sampling distribution of the sample mean? a) The mean of the sampling distribution is...
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...interpreting data. In the accompanying stem-and-leaf diagram, the values in the stem and leaf portions represent 10s and 1s digits, respectively. The stem-and-leaf diagram shows that the distribution is ___________. symmetric positively skewed negatively skewed None of the answers Which of the following is most influenced by outliers? Median Mode 75th percentile Mean serial correlation is typically observed in: sparse data outliers cross-sectional data time series data n the sample regression equation what is ? The value of y when x = 0 The predicted value of y, given a specific x value The slope of the equation The y-intercept bias can occur in sampling. Bias refers to _____________________. the use of cluster sampling instead of stratified random sampling the division of the population into overlapping groups the tendency of a sample statistic to systematically...
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