The Logic of Sampling. Methods of Sampling Nonprobability samplesNonprobability samples –Used often in Qualitative Research Probability or random samplesProbability.

Slides:

Advertisements

Similar presentations

Chapter 10: Sampling and Sampling Distributions

Advertisements

Sampling Teaching Research Methods: Resources for HE Social Sciences Practitioners.

Research Methods in MIS: Sampling Design

Taejin Jung, Ph.D. Week 8: Sampling Messages and People

MISUNDERSTOOD AND MISUSED

Topics: Inferential Statistics

DATA COLLECTION AND SAMPLING MKT525. DATA COLLECITON 4 Telephone 4 Mail 4 Panels 4 Personal Interviews 4 Internet.

Sampling-big picture Want to estimate a characteristic of population (population parameter). Estimate a corresponding sample statistic Sample must be representative.

Research Methods Chapter 5: Sampling. Sampling Purpose: To draw enough of something to make your findings generalizable Purpose: To draw enough of something.

7-1 Chapter Seven SAMPLING DESIGN. 7-2 Sampling What is it? –Drawing a conclusion about the entire population from selection of limited elements in a.

Social Research Methods: Qualitative and Quantitative Approaches, 5e This multimedia product and its contents are protected under copyright law. The following.

Chapter 8 Selecting Research Participants. DEFINING A POPULATION BY A RANDOM NUMBERS TABLE  TABLE 8.1  Partial Page of a Random Numbers Table  ____________________________________________________________________________.

SAMPLING Chapter 7. DESIGNING A SAMPLING STRATEGY The major interest in sampling has to do with the generalizability of a research study’s findings Sampling.

Sampling ADV 3500 Fall 2007 Chunsik Lee. A sample is some part of a larger body specifically selected to represent the whole. Sampling is the process.

CHAPTER 7, the logic of sampling

Chapter Outline  Populations and Sampling Frames  Types of Sampling Designs  Multistage Cluster Sampling  Probability Sampling in Review.

Introduction to Statistics February 21, Statistics and Research Design Statistics: Theory and method of analyzing quantitative data from samples.

McGraw-Hill/Irwin McGraw-Hill/Irwin Copyright © 2009 by The McGraw-Hill Companies, Inc. All rights reserved.

Sampling January 9, Cardinal Rule of Sampling Never sample on the dependent variable! –Example: if you are interested in studying factors that lead.

Sampling. Concerns 1)Representativeness of the Sample: Does the sample accurately portray the population from which it is drawn 2)Time and Change: Was.

Qualitative and Quantitative Sampling

Sampling: Theory and Methods

Foundations of Sociological Inquiry The Logic of Sampling.

Estimation in Sampling!? Chapter 7 – Statistical Problem Solving in Geography.

What are the Odds? Sampling Theory and Logic. Let’s Be Realistic… It’s unlikely you’ll be in a position to do much sampling in your daily work Important.

Variables, sampling, and sample size. Overview  Variables  Types of variables  Sampling  Types of samples  Why specific sampling methods are used.

Basic Sampling & Review of Statistics. Basic Sampling What is a sample?  Selection of a subset of elements from a larger group of objects Why use a sample?

Chapter 11 – 1 Chapter 7: Sampling and Sampling Distributions Aims of Sampling Basic Principles of Probability Types of Random Samples Sampling Distributions.

1 Hair, Babin, Money & Samouel, Essentials of Business Research, Wiley, Learning Objectives: 1.Understand the key principles in sampling. 2.Appreciate.

Sampling Methods.

McGraw-Hill/Irwin © 2003 The McGraw-Hill Companies, Inc.,All Rights Reserved. Part Two THE DESIGN OF RESEARCH.

© 2013 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.

Chapter 7: Sampling and Sampling Distributions

Chapter 7 The Logic Of Sampling. Observation and Sampling Polls and other forms of social research rest on observations. The task of researchers is.

McGraw-Hill/Irwin © 2003 The McGraw-Hill Companies, Inc.,All Rights Reserved. Part Two THE DESIGN OF RESEARCH.

Qualitative and quantitative sampling. Who are they Black/Blue/Green/Red Thin/Bold Smiling/Normal/Sad                        

Chapter 7 The Logic Of Sampling The History of Sampling Nonprobability Sampling The Theory and Logic of Probability Sampling Populations and Sampling Frames.

Introduction to Inferential Statistics Statistical analyses are initially divided into: Descriptive Statistics or Inferential Statistics. Descriptive Statistics.

Sampling Neuman and Robson Ch. 7 Qualitative and Quantitative Sampling.

Determination of Sample Size: A Review of Statistical Theory

Sampling Methods and Sampling Distributions

Learning Objectives Explain the role of sampling in the research process Distinguish between probability and nonprobability sampling Understand the factors.

The Sampling Design. Sampling Design Selection of Elements –The basic idea of sampling is that by selecting some of the elements in a population, we may.

7: Sampling Theory and Methods. 7-2 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials.

Chapter 6: 1 Sampling. Introduction Sampling - the process of selecting observations Often not possible to collect information from all persons or other.

Data Collection & Sampling Dr. Guerette. Gathering Data Three ways a researcher collects data: Three ways a researcher collects data: By asking questions.

15-1 Chapter 15 Sampling Learning Objectives Understand... two premises on which sampling theory is based accuracy and precision for measuring sample.

Chapter 10 Sampling: Theories, Designs and Plans.

7: The Logic of Sampling. Introduction Nobody can observe everything Critical to decide what to observe Sampling –Process of selecting observations Probability.

POLS 7000X STATISTICS IN POLITICAL SCIENCE CLASS 5 BROOKLYN COLLEGE-CUNY SHANG E. HA Leon-Guerrero and Frankfort-Nachmias, Essentials of Statistics for.

INFO 271B LECTURE 9 COYE CHESHIRE Sampling. Agenda Info 271B 2 Non-probability Sampling Probability Sampling Probability Distributions.

CHAPTER 7, THE LOGIC OF SAMPLING. Chapter Outline  A Brief History of Sampling  Nonprobability Sampling  The Theory and Logic of Probability Sampling.

1 Ch. 4, Sampling: How to Select a Few to Represent the Many (Pt. 1) Neumann, pp

Selecting a Sample. outline Difference between sampling in quantitative & qualitative research.

Topics Semester I Descriptive statistics Time series Semester II Sampling Statistical Inference: Estimation, Hypothesis testing Relationships, casual models.

Sampling Concepts Nursing Research. Population  Population the group you are ultimately interested in knowing more about “entire aggregation of cases.

Copyright ©2011 by Pearson Education, Inc. All rights reserved. Chapter 8: Qualitative and Quantitative Sampling Social Research Methods MAN-10 Erlan Bakiev,

Criminal Justice and Criminology Research Methods, Second Edition Kraska / Neuman © 2012 by Pearson Higher Education, Inc Upper Saddle River, New Jersey.

Part Two THE DESIGN OF RESEARCH

Developing the Sampling Plan

Meeting-6 SAMPLING DESIGN

محيط پژوهش محيط پژوهش كه قلمرو مكاني نيز ناميده مي شود عبارت است از مكاني كه نمونه هاي آماري مورد مطالعه از آنجا گرفته مي شود .

Social Research Methods MAN-10 Erlan Bakiev, Ph. D

Sampling Methods.

Sampling Chapter 6.

Sampling: How to Select a Few to Represent the Many

Presentation transcript:

The Logic of Sampling

Methods of Sampling Nonprobability samplesNonprobability samples –Used often in Qualitative Research Probability or random samplesProbability or random samples –Every person has an equal chance of being included in the sample

Sampling of Participants Try to obtain a representative sample – –Representative samples allow us to generalize findings to the larger group Sampling is often not under the control of the researcher in low-constraint (field) research – –Therefore, caution is required in interpreting the results – –Generalize only to similar participants and NOT to the general population

Sampling Terminology Populations Sampling Element Target Population Sampling Frame Parameters and Statistics

Non-Probability Sampling Convenience or Accidental or Haphazard Quota Purposive or Judgmental Snowball

Non-Probability Sampling Deviant cases Sequential Theoretical Use of Informants

Theory & Logic of Probability Sampling Sampling Distribution Central Limit Theorem Sampling Error

The Normal Distribution Represents the actual distribution of naturally occurring data Real distributions do not conform completely to the normal distribution Inferential statistics takes a set of data and “normalizes” it so comparisons can be made

Characteristics of the Normal Distribution Bell shape Unimodal Mean is located at the center of the bell curve Area under the curve is 100% of the data The 50th percentile or the median, is the same value as the mean

The Standard Deviation and the Normal Distribution Direct relationship between the standard deviation and the curve The same number of observations will always fall within the same standard deviation units from the mean of the distribution – –68% lie within -1 to +1 s.d.’s from the mean – –95% lie within -2 to +2 s.d.’s from the mean – –99.8% lie within -3 to +3 s.d.’s from the mean

Probability Sampling Simple Random Sample Systematic Sampling Stratified Sampling

Probability Sampling Cluster Sampling – –Within Household Sampling – –Probability Proportionate to Size (PPS) Random-Digit Dialing

Hidden Populations Targeted Sampling Respondent Drive Sampling

Sample Size Degree of precision or accuracy needed – –Larger samples will provide more precise estimates of population parameters Variability or diversity in the population Number of different variables Costs and time constraints The larger the sample, the more narrow the confidence intervals

Drawing Inferences Inferential Statistics Sampling Error