# Non-random/non-probability sampling designs in quantitative research

Save this PDF as:

Size: px
Start display at page:

## Transcription

3 208 RESEARCH METHODOLOGY Selecting a sample with snowball sampling FIGURE 12.7 Snowball sampling Snowball sampling Snowball sampling is the process of selecting a sample using networks. To start with, a few individuals in a group or organisation are selected and the required information is collected from them. They are then asked to identify other people in the group or organisation, and the people selected by them become a part of the sample. Information is collected from them, and then these people are asked to identify other members of the group and, in turn, those identified become the basis of further data collection (Figure 12.7).This process is continued until the required number or a saturation point has been reached, in terms of the information being sought. This sampling technique is useful if you know little about the group or organisation you wish to study, as you need only to make contact with a few individuals, who can then direct you to the other members of the group. This method of selecting a sample is useful for studying communication patterns, decision making or diffusion of knowledge within a group. There are disadvantages to this technique, however. The choice of the entire sample rests upon the choice of individuals at the first stage. If they belong to a particular faction or have strong biases, the study may be biased. Also, it is difficult to use this technique when the sample becomes fairly large. Systematic sampling design: a 'mixed' design Systematic sampling has been classified as a 'mixed' sampling design because it has the characteristics ofboth random and non-random sampling designs. In systematic sampling the sampling frame is first divided into a number of segments called intervals. Then, from the first interval, using the SRS technique, one element is selected. The selection of subsequent elements from other intervals is dependent upon the order of the element selected in the first interval. If in the first interval it is the fifth element, the fifth element

4 CHAPTER 12: SELECTING A SAMPLE 209 of each subsequent interval will be chosen. Notice that from the first interval the choice of an element is on a random basis, but the choice of the elements from subsequent intervals is dependent upon the choice from the first, and hence cannot be classified as a random sample. The procedure used in systematic sampling is presented in Figure Step 1 Prepare a list of all the elements in the study population (N}. Step 2 Decide on the sample size (n). Step 3 Determine the width of the interval (k) =total popul~tion sample s1ze Step 4 Using the SRS, select an element from the first interval (nth order). Step 5 Select the same order element from each subsequent interval. FIGURE 12.8 The procedure for selecting a systematic sample Although the general procedure for selecting a sample by the systematic sampling technique is described above, you can deviate from it by selecting a different element from each interval with the SRS technique. By adopting this, systematic sampling can be classified under probability sampling designs. To select a random sample you must have a sampling frame (Figure 12.9). Sometimes this is impossible, or obtaining one may be too expensive. However, in real life there are situations where a kind of sampling frame exists, for example records of clients in an agency, enrolment lists of students in a school or university, electoral lists of people living in an area, or records of the staff employed in an organisation. All these can be used as a sampling frame to select a sample with the systematic sampling technique. This convenience of having a 'ready-made' sampling frame may be at a price: in some cases it may not truly be a random listing. Mostly these lists are in alphabetical order, based upon a number assigned to a case, or arranged in a way that is convenient to the users of the records. If the 'width of an interval' is large, say, 1 in 30 cases, and if the cases are arranged in alphabetical order, you could preclude some whose surnames start with the same letter or some adjoining letter may not be included at all. Suppose there are 50 students in a class and you want to select 10 students using the systematic sampling technique. The first step is to determine the width of the interval (50/10 = 5). This means that from every five you need to select one element. Using the SRS technique, from the first interval (1-5 elements), select one of the elements. Suppose you selected the third element. From the rest of the intervals you would select every third element. The calculation of sample size Students and others often ask: 'How big a sample should I select?', 'What should be my sample size?' and 'How many cases do I need?' Basically, it depends on what you want to

5 210 RESEARCH METHODOLOGY Systematic sampling Sampling frame Sample selec ted ~ 2 (ij > 8.l!l 13 4 c []] c: 16 ~ 41 5 ~ [}]] []] 21 ~ ~ ~ 48 FIGURE 12.9 Systematic sampling do with the findings and what type of relationships you want to establish. Your purpose in undertaking research is the main determinant of the level of accuracy required in the results, and this level of accuracy is an important determinant of sample size. However, in qualitative research, as the main focus is to explore or describe a situation, issue, process or phenomenon, the question of sample size is less important. You usually collect data till you think you have reached saturation point in terms of discovering new information. Once you think you are not getting much new data from your respondents, you stop collecting further information. Of course, the diversity or heterogeneity in what you are trying to find out about plays an important role in how fast you will reach saturation point. And remember: the greater the heterogeneity or diversity in what you are trying to find out about, the greater the number of respondents you need to contact to reach saturation point. In determining the size of your sample for quantitative studies and in particular for cause-and-effect studies, you need to consider the following: At what level of confidence do you want to test your results, findings or hypotheses? With what degree of accuracy do you wish to estimate the population parameters? What is the estimated level of variation (standard deviation), with respect to the main variable you are studying, in the study population? Answering these questions is necessary regardless of whether you intend to determine the sample size yourself or have an expert do it for you. The size of the sample is important for testing a hypothesis or establishing an association, but for other studies the general rule is: the

6 CHAPTER 12: SELECTING A SAMPLE 211 larger the sample size, the more accurate your estimates. In practice, your budget determines the size of your sample. Your skills in selecting a sample, within the constraints of your budget, lie in the way you select your elements so that they effectively and adequately represent your sampling population. To illustrate this procedure let us take the example of a class. Suppose you want to find out the average age of the students within an accuracy of 0.5 of a year; that is, you can tolerate an error of half a year on either side of the true average age. Let us also assume that you want to find the average age within half a year of accuracy at the 95 per cent confidence level; that is, you want to be 95 per cent confident about your findings. The formula (from statistics) for determining the confidence limits is X- ' --+( X_ to.os ) J;l a where x = estimated value of the population mean x = average age calculated from the sample t 0 _ 05 = value oft at 95 per cent confidence level cri.yll = standard error a = standard deviation ll = sample size.y = square root If we decide to tolerate an error of half a year, that means - a X± (t o.os) J;l 0.5 :x± o.5 - a in other words we would like x ± (t oos) J;l or (1.96*) cr/.yll = 0.5_(value of t 0 05 = 1.96). _/ _ X CJ.. "Yl *t-value from the following table Level t-value There is only one unknown quantity in the above equation, that is cr.

7 212 RESEARCH METHODOLOGY Now the main problem is to find the value of cr without having to collect data. This is the biggest problem in estimating the sample size. Because of this it is important to know as much as possible about the study population. The value of cr can be found by one of the following: 1 guessing; 2 consulting an expert; 3 obtaining the value of cr from previous comparable studies; or 4 carrying out a pilot study to calculate the value. Let us assume that cr is 1 year. Then. I _ 1.96 X 1 'Ill = 3.92., :. TJ= 15.37, say, 16 Hence, to determine the average age of the class at a level of95 per cent accuracy (assuming cr = 1 year) with half a year of error, a sample of at least 16 students is necessary. Now assume that, instead of 95 per cent, you want to be 99 per cent confident about the estimated age, tolerating an error of half a year. Then -,/TJ = X = 5.15 :. Tj = 26.54, say, 27 Hence, if you want to be 99 per cent confident and are willing to tolerate an error of half a year, you need to select a sample of 27 students. Similarly, you can calculate the sample size with varying values of cr. Remember the golden rule: the greater is the sample size, the more accurately your findings will riflect the 'true' picture. Sampling in qualitative research As the main aim in qualitative enquiries is to explore the diversity, sample size and sampling strategy do not play a significant role in the selection of a sample. If selected carefully, diversity can be extensively and accurately described on the basis of information obtained even from one individual. All non-probability sampling designs - purposive, judgemental, expert, accidental and snowball - can also be used in qualitative research with two differences: 1 In quantitative studies you collect information from a predetermined number of people but, in qualitative research, you do not have a sample size in mind. Data collection based upon

8 CHAPTER 12: SELECTING A SAMPLE 21.3 a predetermined sample size and the saturation point distinguishes their use in quantitative and qualitative research. 2 In quantitative research you are guided by your desire to select a random sample, whereas in qualitative research you are guided by your judgement as to who is likely to provide you with the 'best' information. The concept of saturation point in qualitative research e As you already know, in qualitative research data is usually collected to a point where you are not getting new information or it is negligible - the data saturation point. This stage determines the sample size. It is important for you to keep in mind that the concept of data saturation point is highly subjective. It is you who are collecting the data and decide when you have attained the saturation point in your data collection. How soon you reach the saturation point depends upon how diverse is the situation or phenomenon that you are studying. The greater the diversity, the greater the number of people from whom you need to collect the information to reach the saturation point. The concept of saturation point is more applicable to situations w here you are collecting information on a one-to-one basis. Where the information is collected in a collective format such as focus groups, community forums or panel discussions, you strive to gather as diverse and as much information as possible. When no new information is emerging it is assumed that you have reached the saturation point. Summary ~e re lg ty tn 1- rt, m In this chapter you have learnt about sampling, the process of selecting a few elements from a sampling population. Sampling, in a way, is a trade-off between accuracy and resources. Through sampling you make an estimate about the information of interest. You do not find the true population mean. Two opposing philosophies underpin the selection of sampling units in quantitative and qualitative research. In quantitative studies a sample is supposed to be selected in such a way that it represents the study population, which is achieved through randomisation. However, the selection of a sample in qualitative research is guided by your judgement as to who is likely to provide you with complete and diverse information. This is a non-random process. Sample size does not occupy a significant place in qualitative research and it is determined by the data saturation point while collecting data instead of being fixed in advance. In quantitative research, sampling is guided by three principles, one of which is that the greater the sample size, the more accurate the estimate of the true population mean, given that everything else remains the same. The inferences drawn from a sample can be affected by both the size of the sample and the extent of variation in the sampling population.

9 214 RESEARCH METHODOLOGY Sampling designs can be classified as random/probability sampling designs, non-random; non-probability sampling designs and 'mixed' sampling designs. For a sample to be called a random sample, each element in the study population must have an equal and independent chance of selection. Three random designs were discussed: simple random sampling, stratified random sampling and cluster sampling. The procedures for selecting a sample using these designs were detailed step by step. The use of the fishbowl technique, the table of random numbers and specifically designed computer programs are three commonly used methods of selecting a probability sample. There are five non-probability sampling designs: quota, accidental, judgemental, expert and snowball. Each is used for a different purpose and in different situations in both quantitative and qualitative studies. In quantitative studies their application is underpinned by the sample size whereas the data saturation point determines the 'sample size' in qualitative studies. Systematic sampling is classified under the 'mixed' category as it has the properties of both probability and non-probability sampling designs. The last section of the chapter described determinants of, and procedures for, calculating sample size. Although it might be slightly more difficult for the beginner, this was included to make you aware of the determinants involved as questions relating to this area are so commonly asked. In qualitative research, the question of sample size is less important, as your aim is to explore, not quantify, the extent of variation for which you are guided by reaching saturation point in terms of new findings. I / For You to Think About ~ Refamiliarise yourself with the keywords listed at the beginning of this chapter and if you are uncertain about the meaning or application of any of them revisit these in the chapter before moving on. ~ Consider the implications of selecting a sample based upon your choice as a researcher and how you could make sure that you do not introduce bias. ~ In the absence of a sampling frame for employees of a large organisation, which sampling design would you use to select a sample of 219 people? Explain why you would choose this design and the process you would undertake to ensure that the sample is representative. ~ From your own area of interest, identify examples of where cluster sampling could be applied. ~ What determines sample size in qualitative research? ~ What is the data saturation point in qualitative studies?

### Survey Sampling. Know How No 9 guidance for research and evaluation in Fife. What this is about? Who is it for? What do you need to know?

guidance for research and evaluation in Fife What this is about? Sampling allows you to draw conclusions about a particular population by examining a part of it. When carrying out a survey, it is not usually

### Statistical Inference

Statistical Inference Idea: Estimate parameters of the population distribution using data. How: Use the sampling distribution of sample statistics and methods based on what would happen if we used this

### Data network for better European organic market information SAMPLING. and its relevance for sound data collection

Data network for better European organic market information SAMPLING and its relevance for sound data collection OrganicDataNetwork Workshop, Bari, July 10 & 11, 2014 Corinna Feldmann, University of Kassel

### NON-PROBABILITY SAMPLING TECHNIQUES

NON-PROBABILITY SAMPLING TECHNIQUES PRESENTED BY Name: WINNIE MUGERA Reg No: L50/62004/2013 RESEARCH METHODS LDP 603 UNIVERSITY OF NAIROBI Date: APRIL 2013 SAMPLING Sampling is the use of a subset of the

### Chapter 8: Quantitative Sampling

Chapter 8: Quantitative Sampling I. Introduction to Sampling a. The primary goal of sampling is to get a representative sample, or a small collection of units or cases from a much larger collection or

### TYPES OF SAMPLING. 2. Types of Non-probability Sample: There are the following four types of nonprobability PROBABILITY SAMPLING

TYPES OF SAMPLING 1. Types or Techniques Probability Sampling: There are a number of techniques of taking Probability sample. But here only six important techniques have been discussed as follows: 1. Simple

About Sampling TABLE OF CONTENTS About Sampling... 1 Why is SAMPLING important?... 1 Common Language... 1 Probability & Nonprobability Sampling... 1 Sampling Methods... 2 Simple Random Sample (SRS)...

### Survey Process White Paper Series The Six Steps in Conducting Quantitative Marketing Research

Survey Process White Paper Series The Six Steps in Conducting Quantitative Marketing Research POLARIS MARKETING RESEARCH, INC. 1455 LINCOLN PARKWAY, SUITE 320 ATLANTA, GEORGIA 30346 404.816.0353 www.polarismr.com

### DETERMINING SURVEY SAMPLE SIZE A SIMPLE PLAN

DETERMINING SURVEY SAMPLE SIZE A SIMPLE PLAN Prepared by Market Directions Market Directions B O S T O N 617-323-1862 800-475-9808 www.marketdirectionsmr.com info@marketdirectionsmr.com DETERMING SAMPLE

### SAMPLING METHODS. Chapter 5

SAMPLING METHODS Chapter 5 1 LEARNING OBJECTIVES Reasons for sampling Different sampling methods Probability & non probability sampling Advantages & disadvantages of each sampling method 2 SAMPLING A sample

### 1) Overview 2) Sample or Census 3) The Sampling Design Process i. Define the Target Population ii. Determine the Sampling Frame iii.

1) Overview 2) Sample or Census 3) The Sampling Design Process i. Define the Target Population ii. Determine the Sampling Frame iii. Select a Sampling Technique iv. Determine the Sample Size v. Execute

### Sampling: Design and Procedures

MBACATÃ“LICA JAN/APRIL 2006 Marketing Research Fernando S. Machado Week 6 Sampling: Design and Procedures Sampling: Sample Size Determination Data Preparation 1 Sampling: Design and Procedures The Sampling

### Basic Research Progress

Mgt 540 Research Methods Sampling Issues 1 Basic Research Progress Explorative - Descriptive (Qualitative) 1. Framework / Domain extant knowledge for reference 2. Research Design 3. Data collection / presentation

### Welcome back to EDFR 6700. I m Jeff Oescher, and I ll be discussing quantitative research design with you for the next several lessons.

Welcome back to EDFR 6700. I m Jeff Oescher, and I ll be discussing quantitative research design with you for the next several lessons. I ll follow the text somewhat loosely, discussing some chapters out

### SAMPLING & INFERENTIAL STATISTICS. Sampling is necessary to make inferences about a population.

SAMPLING & INFERENTIAL STATISTICS Sampling is necessary to make inferences about a population. SAMPLING The group that you observe or collect data from is the sample. The group that you make generalizations

### Sampling & Sample Size Estimation

Sampling & Sample Size Estimation Moazzam Ali MD, PhD, MPH Department of Reproductive Health and Research World Health Organization Geneva, Switzerland Presented at: GFMER September 16, 2014 Topics to

### Survey Process White Paper Series Five Steps in Creating a Survey Sampling Plan

Survey Process White Paper Series Five Steps in Creating a Survey Sampling Plan POLARIS MARKETING RESEARCH, INC. 1455 LINCOLN PARKWAY, SUITE 320 ATLANTA, GEORGIA 30346 404.816.0353 www.polarismr.com ii

### Sampling in Marketing Research

Sampling in Marketing Research 1 Basics of sampling I A sample is a part of a whole to show what the rest is like. Sampling helps to determine the corresponding value of the population and plays a vital

### Introduction to Sampling. Dr. Safaa R. Amer. Overview. for Non-Statisticians. Part II. Part I. Sample Size. Introduction.

Introduction to Sampling for Non-Statisticians Dr. Safaa R. Amer Overview Part I Part II Introduction Census or Sample Sampling Frame Probability or non-probability sample Sampling with or without replacement

### Experimental data and survey data

Experimental data and survey data An experiment involves the collection of measurements or observations about populations that are treated or controlled by the experimenter. A survey is an examination

### MAT140: Applied Statistical Methods Summary of Calculating Confidence Intervals and Sample Sizes for Estimating Parameters

MAT140: Applied Statistical Methods Summary of Calculating Confidence Intervals and Sample Sizes for Estimating Parameters Inferences about a population parameter can be made using sample statistics for

### Sampling & Confidence Intervals

Sampling & Confidence Intervals Mark Lunt Arthritis Research UK Centre for Excellence in Epidemiology University of Manchester 18/10/2016 Principles of Sampling Often, it is not practical to measure every

### 5.3 SAMPLING Introduction Overview on Sampling Principles. Sampling

Sampling 5.3 SAMPLING 5.3.1 Introduction Data for the LULUCF sector are often obtained from sample surveys and typically are used for estimating changes in land use or in carbon stocks. National forest

### Appendix Methodology and Statistics

Appendix Methodology and Statistics Introduction Science and Engineering Indicators (SEI) contains data compiled from a variety of sources. This appendix explains the methodological and statistical criteria

### EAA492/6: FINAL YEAR PROJECT DEVELOPING QUESTIONNAIRES PART 2 A H M A D S H U K R I Y A H A Y A E N G I N E E R I N G C A M P U S U S M

EAA492/6: FINAL YEAR PROJECT DEVELOPING QUESTIONNAIRES PART 2 1 A H M A D S H U K R I Y A H A Y A E N G I N E E R I N G C A M P U S U S M CONTENTS Reliability And Validity Sample Size Determination Sampling

### Answer keys for Assignment 10: Measurement of study variables

Answer keys for Assignment 10: Measurement of study variables (The correct answer is underlined in bold text) 1. In a study, participants are asked to indicate the type of pet they have at home (ex: dog,

### CHAPTER 3. Research methodology

CHAPTER 3 Research methodology 3.1 INTRODUCTION This chapter deals with the research methodology of the study, including the research design, setting, population, sample and data-collection instrument.

### BUSINESS OCR LEVEL 3 CAMBRIDGE TECHNICAL. Cambridge TECHNICALS MARKET RESEARCH IN BUSINESS CERTIFICATE/DIPLOMA IN H/502/5427 LEVEL 3 UNIT 10

Cambridge TECHNICALS OCR LEVEL 3 CAMBRIDGE TECHNICAL CERTIFICATE/DIPLOMA IN BUSINESS MARKET RESEARCH IN BUSINESS H/502/5427 LEVEL 3 UNIT 10 GUIDED LEARNING HOURS: 60 UNIT CREDIT VALUE: 10 MARKET RESEARCH

### Research Design Concepts. Independent and dependent variables Data types Sampling Validity and reliability

Research Design Concepts Independent and dependent variables Data types Sampling Validity and reliability Research Design Action plan for carrying out research How the research will be conducted to investigate

### Chapter 7 Multiple Choice Questions (The answers are provided after the last question.)

Chapter 7 Multiple Choice Questions (The answers are provided after the last question.) 1. When each member of a population has an equally likely chance of being selected, this is called: a. A nonrandom

### Sample size and sampling methods

Sample size and sampling methods Ketkesone Phrasisombath MD, MPH, PhD (candidate) Faculty of Postgraduate Studies and Research University of Health Sciences GFMER - WHO - UNFPA - LAO PDR Training Course

### Sampling Procedures Y520. Strategies for Educational Inquiry. Robert S Michael

Sampling Procedures Y520 Strategies for Educational Inquiry Robert S Michael RSMichael 2-1 Terms Population (or universe) The group to which inferences are made based on a sample drawn from the population.

### Inference, Sampling, and Confidence. Inference. Inference

Inference, Sampling, and Confidence Inference defined Sampling Statistics and parameters Sampling distribution Confidence and standard error Estimation Precision and accuracy Estimating sample size 1 Inference

### Educational Research - Chapter 4 Airasian and Gay

How could this have been avoided? Today General sampling issues Quantitative sampling Random Non-random Qualitative sampling In Other Words How many subjects are enough? Does it really matter how you choose

### Section 2: Ten Tools for Applying Sociology

Section 2: Ten Tools for Applying Sociology CHAPTER 2.6: DATA COLLECTION METHODS QUICK START: In this chapter, you will learn The basics of data collection methods. To know when to use quantitative and/or

### Social Studies 201 Notes for November 19, 2003

1 Social Studies 201 Notes for November 19, 2003 Determining sample size for estimation of a population proportion Section 8.6.2, p. 541. As indicated in the notes for November 17, when sample size is

### Chapter 7 Sampling (Reminder: Don t forget to utilize the concept maps and study questions as you study this and the other chapters.

Chapter 7 Sampling (Reminder: Don t forget to utilize the concept maps and study questions as you study this and the other chapters.) The purpose of Chapter 7 it to help you to learn about sampling in

### Sampling: What is it? Quantitative Research Methods ENGL 5377 Spring 2007

Sampling: What is it? Quantitative Research Methods ENGL 5377 Spring 2007 Bobbie Latham March 8, 2007 Introduction In any research conducted, people, places, and things are studied. The opportunity to

### INTERNATIONAL STANDARD ON AUDITING (UK AND IRELAND) 530 AUDIT SAMPLING AND OTHER MEANS OF TESTING CONTENTS

INTERNATIONAL STANDARD ON AUDITING (UK AND IRELAND) 530 AUDIT SAMPLING AND OTHER MEANS OF TESTING CONTENTS Paragraph Introduction... 1-2 Definitions... 3-12 Audit Evidence... 13-17 Risk Considerations

### Why Sample? Why not study everyone? Debate about Census vs. sampling

Sampling Why Sample? Why not study everyone? Debate about Census vs. sampling Problems in Sampling? What problems do you know about? What issues are you aware of? What questions do you have? Key Sampling

### Content Sheet 7-1: Overview of Quality Control for Quantitative Tests

Content Sheet 7-1: Overview of Quality Control for Quantitative Tests Role in quality management system Quality Control (QC) is a component of process control, and is a major element of the quality management

### A GUIDE TO SAMPLING & STATISTICAL RELIABILITY

July 2009 Technical Note 5 A GUIDE TO SAMPLING & STATISTICAL RELIABILITY The word survey is used most often to describe a method of gathering information from a sample of individuals. This sample is usually

### DESCRIPTIVE RESEARCH DESIGNS

DESCRIPTIVE RESEARCH DESIGNS Sole Purpose: to describe a behavior or type of subject not to look for any specific relationships, nor to correlate 2 or more variables Disadvantages since setting is completely

### INTERNATIONAL STANDARD ON AUDITING 530 AUDIT SAMPLING AND OTHER MEANS OF TESTING CONTENTS

INTERNATIONAL STANDARD ON AUDITING 530 AUDIT SAMPLING AND OTHER MEANS OF TESTING (Effective for audits of financial statements for periods beginning on or after December 15, 2004) CONTENTS Paragraph Introduction...

### the law of inertia of large numbers, which states that large groups are more stable than small ones. Applied to research, the first law means that a g

T O P I C 7 Data gathering 2 Preview Introduction This topic is a continuation of topic 6 and is concerned with the theory and methodology of sampling. Sampling forms a foundation to methods of data gathering

### Selecting Research Participants

C H A P T E R 6 Selecting Research Participants OBJECTIVES After studying this chapter, students should be able to Define the term sampling frame Describe the difference between random sampling and random

### Developing and implementing surveys

Developing and implementing surveys This fact sheet points to some key considerations in developing and implementing surveys to ensure you get interesting and useful information and data. What are surveys?

### Research Approaches: Quantitative Methodology A potted guide to Surveys by Questionnaire. Introduction

Research Approaches: Quantitative Methodology A potted guide to Surveys by Questionnaire Introduction 1. This paper describes what is probably both the most statistically reliable and cost effective quantitative

### Sampling. COUN 695 Experimental Design

Sampling COUN 695 Experimental Design Principles of Sampling Procedures are different for quantitative and qualitative research Sampling in quantitative research focuses on representativeness Sampling

### 1.1 Research in Geography [Meaning & Importance]

Department of Geography GEO 271 Everything is related to everything else, but near things are more related than distant things. - Waldo Tobler s First Law of Geography 1.1 Research in Geography [Meaning

### OPERATIONAL SELECTION POLICY OSP0 THE SELECTION OF CASE FILES: SAMPLING TECHNIQUES

OPERATIONAL SELECTION POLICY OSP0 THE SELECTION OF CASE FILES: SAMPLING TECHNIQUES Revised October 2005 1 Authority The National Archives' Acquisition and Disposition Policies announced the Archives intention

### Sampling Exercise. ESP178 Research Methods Professor Susan Handy 2/4/16

Sampling Exercise ESP178 Research Methods Professor Susan Handy 2/4/16 Types of Sampling Type Probability sampling i.e. random Non-probability sampling i.e. non-random Definition Every element in the population

### SAMPLING SIZE DETERMINATION IN FARMER SURVEYS. ICRAF Research Support Unit. Technical Note 4. Ric Coe Version January 1996

ICRAF Research Support Unit Technical Note 4 SAMPLING SIZE DETERMINATION IN FARMER SURVEYS Ric Coe Version January 1996 ICRAF World Agroforestry Centre PO Box 30677, Nairobi, Kenya Telephone : +54 54 000

### RESEARCH: DESIGN AND METHODS (II)

RESEARCH: DESIGN AND METHODS (II) Division for Postgraduate Studies (DPGS) Post-graduate Enrolment and Throughput Program Dr. Christopher E. Sunday and Dr Brian van Wyk From last meeting. Difference between

### 2 STATISTICAL INVESTIGATION INTRODUCTION ORGANISATION OF STATISTICAL INVESTIGATION

2 STATISTICAL INVESTIGATION INTRODUCTION By the term investigation (or enquiry) we mean the search for information or knowledge. Statistical investigation, thus, implies search for knowledge with the help

### Sampling Distributions and the Central Limit Theorem

135 Part 2 / Basic Tools of Research: Sampling, Measurement, Distributions, and Descriptive Statistics Chapter 10 Sampling Distributions and the Central Limit Theorem In the previous chapter we explained

### Task force on quality of BCS data. Analysis of sample size in consumer surveys

Task force on quality of BCS data Analysis of sample size in consumer surveys theoretical considerations and factors determining minimum necessary sample sizes, link between country size and sample size

### Dr A Shaghaghi. Critical appraisal. Dr A Shaghaghi. Tabriz University of Medical Sciences

Critical appraisal Tabriz University of Medical Sciences What does critical appraisal mean? This is the process by which a reader can evaluate a piece of written material and assess whether it possesses

### Descriptive Methods Ch. 6 and 7

Descriptive Methods Ch. 6 and 7 Purpose of Descriptive Research Purely descriptive research describes the characteristics or behaviors of a given population in a systematic and accurate fashion. Correlational

### 5.1 Identifying the Target Parameter

University of California, Davis Department of Statistics Summer Session II Statistics 13 August 20, 2012 Date of latest update: August 20 Lecture 5: Estimation with Confidence intervals 5.1 Identifying

### Introduction... 3. Qualitative Data Collection Methods... 7 In depth interviews... 7 Observation methods... 8 Document review... 8 Focus groups...

1 Table of Contents Introduction... 3 Quantitative Data Collection Methods... 4 Interviews... 4 Telephone interviews... 5 Face to face interviews... 5 Computer Assisted Personal Interviewing (CAPI)...

### CEIOPS-DOC-37/09. (former CP 43) October 2009

CEIOPS-DOC-37/09 CEIOPS Advice for Level 2 Implementing Measures on Solvency II: Technical Provisions Article 86 f Standards for Data Quality (former CP 43) October 2009 CEIOPS e.v. Westhafenplatz 1-60327

### Chapter 3. Sampling. Sampling Methods

Oxford University Press Chapter 3 40 Sampling Resources are always limited. It is usually not possible nor necessary for the researcher to study an entire target population of subjects. Most medical research

### Risk Assessment & Statistical Sampling. By D.Guha Statistical Adviser

Risk Assessment & Statistical Sampling By D.Guha Statistical Adviser Audit Risk Risk assessment is an analytical tool for audit planning and execution. It focuses on areas which are likely to be more error

### Quantitative Research: Reliability and Validity

Quantitative Research: Reliability and Validity Reliability Definition: Reliability is the consistency of your measurement, or the degree to which an instrument measures the same way each time it is used

### Basic Principles of Survey Design. Thomas Lindsay Andrew Sell

Basic Principles of Survey Design Thomas Lindsay Andrew Sell Introductions Name, Institution, why are you here? Survey Review 5 minutes Political Participation and Attitudes Survey What is the research

### Experimental Designs. Y520 Strategies for Educational Inquiry

Experimental Designs Y520 Strategies for Educational Inquiry Experimental designs-1 Research Methodology Is concerned with how the design is implemented and how the research is carried out. The methodology

### In this chapter, you will learn to use descriptive statistics to organize, summarize, analyze, and interpret data for contract pricing.

3.0 - Chapter Introduction In this chapter, you will learn to use descriptive statistics to organize, summarize, analyze, and interpret data for contract pricing. Categories of Statistics. Statistics is

### Hypothesis Testing Level I Quantitative Methods. IFT Notes for the CFA exam

Hypothesis Testing 2014 Level I Quantitative Methods IFT Notes for the CFA exam Contents 1. Introduction... 3 2. Hypothesis Testing... 3 3. Hypothesis Tests Concerning the Mean... 10 4. Hypothesis Tests

### Guided Reading 9 th Edition. informed consent, protection from harm, deception, confidentiality, and anonymity.

Guided Reading Educational Research: Competencies for Analysis and Applications 9th Edition EDFS 635: Educational Research Chapter 1: Introduction to Educational Research 1. List and briefly describe the

### primary data (collect the data yourself) secondary data (use data collected by others)

Slide 3.1 Chapter 9: Data collection and sampling methods Data collection primary data (collect the data yourself) secondary data (use data collected by others) Examine secondary sources first paper sources

### STUDYING SOCIETY AQA GCSE SOCIOLOGY UNIT 1 MAY 2013

STUDYING SOCIETY AQA GCSE SOCIOLOGY UNIT 1 MAY 2013 THE SOCIOLOGICAL APPROACH Sociology explores the social factors that shape human behavior and the way that society influences our daily lives. Sociologists

### GCSE Statistics Revision notes

GCSE Statistics Revision notes Collecting data Sample This is when data is collected from part of the population. There are different methods for sampling Random sampling, Stratified sampling, Systematic

### Notes and Comments I INTRODUCTION

Economic and Social Review, Vol. 10, No. 2, January, 1979, pp. 169-174. Notes and Comments RANSAM: A Random Sample Design for Ireland BRENDAN J. WHELAN The Economic and Social Research Institute, Dublin

### Preliminaries to Sampling

Preliminaries to Sampling In social science research involving Statistical analysis, we make all our choices as explicitly as possible. When we come to choose elements in a piece of research, one of the

### Introduction to Hypothesis Testing

I. Terms, Concepts. Introduction to Hypothesis Testing A. In general, we do not know the true value of population parameters - they must be estimated. However, we do have hypotheses about what the true

### Practical Advice for Selecting Sample Sizes

Practical Advice for Selecting Sample Sizes William Fairbairn and Adam Kessler. Sample Size Calculator by Richard Tanburn. May 2015 Links updated Sept. 16 1 Introduction Many project managers today have

### 11.2 POINT ESTIMATES AND CONFIDENCE INTERVALS

11.2 POINT ESTIMATES AND CONFIDENCE INTERVALS Point Estimates Suppose we want to estimate the proportion of Americans who approve of the president. In the previous section we took a random sample of size

### These days, surveys are used everywhere and for many reasons. For example, surveys are commonly used to track the following:

The previous handout provided an overview of study designs. The two broad classifications discussed were randomized experiments and observational studies. In this handout, we will briefly introduce a specific

### 2. Sampling and Measurement

2. Sampling and Measurement Variable a characteristic that can vary in value among subjects in a sample or a population. Types of variables Categorical (also called qualitative) Quantitative (There are

### Techniques for data collection

Techniques for data collection Technical workshop on survey methodology: Enabling environment for sustainable enterprises in Indonesia Hotel Ibis Tamarin, Jakarta 4-6 May 2011 Presentation by Mohammed

### Sample Size Determination

Sample Size Determination Population A: 10,000 Population B: 5,000 Sample 10% Sample 15% Sample size 1000 Sample size 750 The process of obtaining information from a subset (sample) of a larger group (population)

### Critical appraisal of qualitative research. Slides by Sarah Lawson

Critical appraisal of qualitative research Slides by Sarah Lawson 1 Learning objectives Understand the principles of critical appraisal and its role in evidence based practice Be aware of the key elements

Research and Research Methods What we will cover: Formal vs. Informal Qualitative vs. Quantitative Primary vs. Secondary Focus Groups In-Depth Interviews Intercept Interviews 1 Research and Research Methods

### Fairfield Public Schools

Mathematics Fairfield Public Schools AP Statistics AP Statistics BOE Approved 04/08/2014 1 AP STATISTICS Critical Areas of Focus AP Statistics is a rigorous course that offers advanced students an opportunity

### Literature Review of Sample Design and Methods

Literature Review of Sample Design and Methods Generally, a researcher employs sampling strategies in order to generate statistics and generalize findings to a larger population. Sampling refers to the

### Sample Size and Power in Clinical Trials

Sample Size and Power in Clinical Trials Version 1.0 May 011 1. Power of a Test. Factors affecting Power 3. Required Sample Size RELATED ISSUES 1. Effect Size. Test Statistics 3. Variation 4. Significance

### Prepared by the Policy, Performance and Quality Assurance Unit (Adults) Tamsin White

Principles of Good Research & Research Proposal Guidee Prepared by the Policy, Performance and Quality Assurance Unit (Adults) Tamsin White March 2006 Principles of Good Research All research is different

### Appendix A: Sampling. Technical Guidance for Calculating Scope 3 Emissions [153]

A Appendix A: Sampling A company needing to collect a large quantity of data for a particular scope 3 category may find it impractical or impossible to collect the data from each activity in the category.

### Reflections on Probability vs Nonprobability Sampling

Official Statistics in Honour of Daniel Thorburn, pp. 29 35 Reflections on Probability vs Nonprobability Sampling Jan Wretman 1 A few fundamental things are briefly discussed. First: What is called probability

### MARKETING RESEARCH AND MARKET INTELLIGENCE (MRM711S) FEEDBACK TUTORIAL LETTER SEMESTER `1 OF 2016. Dear Student

MARKETING RESEARCH AND MARKET INTELLIGENCE (MRM711S) FEEDBACK TUTORIAL LETTER SEMESTER `1 OF 2016 Dear Student Assignment 1 has been marked and this serves as feedback on the assignment. I have included

### MARKETING RESEARCH AND MARKET INTELLIGENCE

MARKETING RESEARCH AND MARKET INTELLIGENCE Course Objectives Upon completion of this unit you will be able to: Evaluate the applicability of the marketing research process to any marketing and market related

### COLLECTION AND PRESENTATION OF DATA

17 COLLECTION AND PRESENTATION OF DATA Getting information on various things around us has become a way of life. Information itself is a major source of knowledge. Without information it is difficult to

### Second Order Linear Nonhomogeneous Differential Equations; Method of Undetermined Coefficients. y + p(t) y + q(t) y = g(t), g(t) 0.

Second Order Linear Nonhomogeneous Differential Equations; Method of Undetermined Coefficients We will now turn our attention to nonhomogeneous second order linear equations, equations with the standard

### POLI 300 Handout #2 N. R. Miller RANDOM SAMPLING. Key Definitions Pertaining to Sampling

POLI 300 Handout #2 N. R. Miller Key Definitions Pertaining to Sampling RANDOM SAMPLING 1. Population: the set of units (in survey research, usually individuals or households), N in number, that are to