SECTION B: METHODS OF INVESTIGATION (300 WORDS). Focus for Section B: Describe the Methods Used to Collect Data Questionnaires – What types of questions?

Slides:



Advertisements
Similar presentations
Chapter 2 Psychological Research Methods and Statistics
Advertisements

MBF3C Lesson #1: Sampling Types and Techniques
Introduction to Sampling for the Implementation of PATs
Lesson Designing Samples. Knowledge Objectives Define population and sample. Explain how sampling differs from a census. Explain what is meant by.
© 2003 Prentice-Hall, Inc.Chap 1-1 Business Statistics: A First Course (3 rd Edition) Chapter 1 Introduction and Data Collection.
QBM117 Business Statistics Statistical Inference Sampling 1.
AP Statistics C5 D2 HW: p.287 #25 – 30 Obj: to understand types of samples and possible errors Do Now: How do you think you collect data?
© 2004 Prentice-Hall, Inc.Chap 1-1 Basic Business Statistics (9 th Edition) Chapter 1 Introduction and Data Collection.
Questions:  Are behavioral measures less valid and less reliable due to the amount of error that can occur during the tests compared to the other measures?
© 2002 Prentice-Hall, Inc.Chap 1-1 Statistics for Managers using Microsoft Excel 3 rd Edition Chapter 1 Introduction and Data Collection.
Sampling.
Statistical Methods Descriptive Statistics Inferential Statistics Collecting and describing data. Making decisions based on sample data.
Basic Business Statistics (8th Edition)
Chapter 4 Selecting a Sample Gay, Mills, and Airasian
SINGLE VARIABLE DATA DEFINITIONS ETC. GENERAL STUFF STATISTICS IS THE PROCESS OF GATHERING, DISPLAYING, AND ANALYZING DATA. DATA CAN BE GATHERED BY CONDUCTING.
Chapter Outline  Populations and Sampling Frames  Types of Sampling Designs  Multistage Cluster Sampling  Probability Sampling in Review.
Aim: How and why does vegetation change across a psammosere at Llobregat delta, Barcelona? Data Collection & Sampling Techniques.
Sample Design.
Sampling learning about.... Why? A population is a defined group of identities that can be the subject of study. The nature of a population can vary greatly,
COLLECTING QUANTITATIVE DATA: Sampling and Data collection
Chapter 1: Introduction to Statistics
Intro Stats Lesson 1.3 B Objectives: SSBAT classify different ways to collect data. SSBAT distinguish between different sampling techniques. Standards:
Sampling Techniques LEARNING OBJECTIVES : After studying this module, participants will be able to : 1. Identify and define the population to be studied.
Chapter 5 Selecting a Sample Gay, Mills, and Airasian 10th Edition
Surveys & Questionnaires. Survey A gathering of a sample of data or opinions considered to be representative of a whole.
Collecting Samples Chapter 2.3 – In Search of Good Data Mathematics of Data Management (Nelson) MDM 4U.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics Seventh Edition By Brase and Brase Prepared by: Lynn Smith.
Chapter 11.0 Why Study Statistics? Statistics is the study of collecting, displaying, analyzing, and interpreting information. Information that was collected.
Prob and Stats, Aug 26 Unit 1 Review - Fundamental Terms and Definitions Book Sections: N/A Essential Questions: What are the building blocks of Statistics,
MDM4U - Collecting Samples Chapter 5.2,5.3. Why Sampling? sampling is done because a census is too expensive or time consuming the challenge is being.
Slide 1 Copyright © 2004 Pearson Education, Inc. Misuses of Statistics  Bad Samples  Small Samples  Misleading Graphs  Pictographs  Distorted Percentages.
© 2012 Cengage Learning. All Rights Reserved. May not be scanned, copied or duplicated, or posted to a publicly accessible website, in whole or in part.
STANDARD ERROR Standard error is the standard deviation of the means of different samples of population. Standard error of the mean S.E. is a measure.
1 Chapter Two: Sampling Methods §know the reasons of sampling §use the table of random numbers §perform Simple Random, Systematic, Stratified, Cluster,
Tahir Mahmood Lecturer Department of Statistics. Outlines: E xplain the role of sampling in the research process D istinguish between probability and.
Chapter 15 Sampling and Sample Size Winston Jackson and Norine Verberg Methods: Doing Social Research, 4e.
An Overview of Statistics Section 1.1. Ch1 Larson/Farber 2 Statistics is the science of collecting, organizing, analyzing, and interpreting data in order.
Copyright © 2005 Brooks/Cole, a division of Thomson Learning, Inc. 1.1 Chapter Five Data Collection and Sampling.
Chapter Five Data Collection and Sampling Sir Naseer Shahzada.
Understanding Basic Statistics Chapter One Organizing Data.
Unit 4B: Geographical Issues Evaluation Paper Aim: To explore the pre-release paper in more depth with a focus on fieldwork and case studies. Objectives:
Notes 1.3 (Part 1) An Overview of Statistics. What you will learn 1. How to design a statistical study 2. How to collect data by taking a census, using.
Chapter 6: 1 Sampling. Introduction Sampling - the process of selecting observations Often not possible to collect information from all persons or other.
Sampling The complete set of people or objects that information is collected from is called the population. Information is normally taken from a small.
LIS 570 Selecting a Sample.
Bangor Transfer Abroad Programme Marketing Research SAMPLING (Zikmund, Chapter 12)
Design of Experiments & Sampling Techniques.
1 of 29Visit UMT online at Prentice Hall 2003 Chapter 1, STAT125Basic Business Statistics STATISTICS FOR MANAGERS University of Management.
Ch1 Larson/Farber 1 Elementary Statistics Math III Introduction to Statistics.
Sampling technique  It is a procedure where we select a group of subjects (a sample) for study from a larger group (a population)
Topics Semester I Descriptive statistics Time series Semester II Sampling Statistical Inference: Estimation, Hypothesis testing Relationships, casual models.
Types of method Quantitative: – Questionnaires – Experimental designs Qualitative: – Interviews – Focus groups – Observation Triangulation.
Unit 3 Investigative Biology. SQA Success Criteria  Explain the difference between random sampling, systematic sampling and stratified sampling.
Sect. 1-3 Experimental Design Objective: SWBAT learn how to design a statistical Study, How to collect data by taking a census using a sampling, using.
Sampling Dr Hidayathulla Shaikh. Contents At the end of lecture student should know  Why sampling is done  Terminologies involved  Different Sampling.
Honors Stats 3 Day 5. Do Now 1) Round 2 Match game! Turn all the cards over and match the examples to the bias 2) Check your HW: Questions??
Geographical Investigations for the Alternative to Coursework (Paper 04) Data Collection.
Collecting Data Backbone of Statistics. It’s all about the Vocabulary!  Population: the entire group that we are interested in  Sample: some.
Collecting Samples Chapter 2.3 – In Search of Good Data Mathematics of Data Management (Nelson) MDM 4U.
STEPS IN RESEARCH PROCESS 1. Identification of Research Problems This involves Identifying existing problems in an area of study (e.g. Home Economics),
AC 1.2 present the survey methodology and sampling frame used
Collecting Data.
SAMPLING (Zikmund, Chapter 12.
Week Three Review.
Business and Management Research
SAMPLING (Zikmund, Chapter 12).
Sample-Sampling-Pengelompokan Data
Sampling Chapter 6.
P3.
Chapter 8 SAMPLING and SAMPLING METHODS
Presentation transcript:

SECTION B: METHODS OF INVESTIGATION (300 WORDS)

Focus for Section B: Describe the Methods Used to Collect Data Questionnaires – What types of questions? (open, closed) – What topics do questions relate to (questions related to income, number of children, how religious someone is, etc) – How many? Interviews – Description of who will be interviewed – How many?

Justification of Methods The method(s) used must be justified and must enable a sufficient quality and quantity of primary data to be produced to allow the fieldwork question to be investigated. Justify: – Why you ask the questions you do – Why you interview the people you interview – Why you sample using the the method you choose

Sampling Techniques Take out Fieldwork Guide Random Systematic Stratified Must be discussed and decided by entire group. Cannot be an individual decision. If 2 group members use one method and 2 others use another, your data is flawed!

What is sampling? A short-cut method for investigating a whole population Data is gathered from a small part of the whole population and used to inform what the whole picture is like

Why Sample? In reality there is simply not enough time, energy, money, labor/manpower, equipment or access to suitable sites to measure every single item or site within the population. Therefore researchers adopt an appropriate sampling strategy to obtain a representative and statistically valid sample of the whole.

Random Sampling What is it? Least biased of all sampling techniques: there is no subjectivity - each member of the total population has an equal chance of selection. Grid System and Random Point: Demonstrate on board

Random Sampling Strengths – Useful in large populations – Avoids bias Limitations – Can lead to poor representation of general population if general areas are underrepresented – What if 75 of your 100 numbers are in Hegewisch?

Systematic Sampling What is it? Choose samples through a systematic or uniform method. – evenly distributed across a spatial context, e.g. every ½ mile – at regular intervals across a temporal context, e.g. every 10 minutes of walking regularly numbered, every 6 th house on the north side of the street

Systematic Sampling Strengths – More straight-forward than random sampling. – Don’t necessarily have to use a grid … sampling just has to be at uniform intervals. – More easily achieves good coverage of study area than random sampling. Limitations – More biased since not all units have an equal chance of selection.

Stratified Sampling What is it? Used when population made up of sub-sets of known size and that comprise different proportions of total population. Stratified sampling ensures results are proportional and representative of the whole. Example, if you know that 75% of population is Hispanic, they should represent 75% of questionnaires Or dividing into 3 or 4 equal groups based on neighborhood.

Stratified Sampling Strengths – Can use with random or systematic sampling (Stratified Random or Stratified Systematic) – With known proportions of sub-sets, can generate results which are more representative of the whole population. – Can make correlations and comparisons between sub- sets. Limitations – To work properly, the proportions of the sub-sets must be known and accurate. – It can be hard to stratify questionnaire data collection - accurate, up to date population data may not be available and it may be hard to identify people's age or social background effectively.

Section B Sample Close Read Take some time to reread Mathew’s Section B. Highlight/label the following: Description of methods Sampling method description Justification of methods (see what she does with copy of questionnaire)