Chapter 4 Topics –Sampling –Hard data –Workflow analysis –Archival documents.

Slides:



Advertisements
Similar presentations
Market research THE TIMES 100.
Advertisements

© 2003 Prentice-Hall, Inc.Chap 1-1 Business Statistics: A First Course (3 rd Edition) Chapter 1 Introduction and Data Collection.
Audit Sampling By David N. Ricchiute
Chapter 5 Information Gathering: Unobtrusive Methods Systems Analysis and Design Kendall & Kendall © 2005 Pearson Prentice Hall.
© 2004 Prentice-Hall, Inc.Chap 1-1 Basic Business Statistics (9 th Edition) Chapter 1 Introduction and Data Collection.
Chapter 4 Sampling and Investigating Hard Data
Copyright © 2011 Pearson Education, Inc. Publishing as Prentice Hall Information Gathering: Unobtrusive Methods Systems Analysis and Design, 8e Kendall.
Chapter 5 Information Gathering: Unobtrusive Methods
Statistical Methods Descriptive Statistics Inferential Statistics Collecting and describing data. Making decisions based on sample data.
11 Populations and Samples.
7-1 Copyright ©2011 Pearson Education, Inc. publishing as Prentice Hall Chapter 7 Sampling and Sampling Distributions Statistics for Managers using Microsoft.
Issues in Sampling and Sample Design – A Managerial Perspective CHAPTER 12 Research Methodologies.
Marketing Research Bangor Transfer Abroad Programme Week Three Review.
Copyright © 2008 by Pearson Education, Inc. Upper Saddle River, New Jersey All rights reserved. John W. Creswell Educational Research: Planning,
Business and Management Research
McGraw-Hill/Irwin McGraw-Hill/Irwin Copyright © 2009 by The McGraw-Hill Companies, Inc. All rights reserved.
Chapter 5 Information Gathering: Unobtrusive Methods Systems Analysis and Design Kendall & Kendall Sixth Edition.
Chapter 13 Data Sources, Sampling, and Data Collection.
Collecting Quantitative Data
CHAPTER 12 – SAMPLING DESIGNS AND SAMPLING PROCEDURES Zikmund & Babin Essentials of Marketing Research – 5 th Edition © 2013 Cengage Learning. All Rights.
Quantitative Research 1: Sampling and Surveys Dr N L Reynolds.
Kendall & KendallCopyright © 2014 Pearson Education, Inc. Publishing as Prentice Hall 5 Kendall & Kendall Systems Analysis and Design, 9e Information Gathering:
System Analysis System Analysis - Mr. Ahmad Al-Ghoul System Analysis and Design.
 Collecting Quantitative  Data  By: Zainab Aidroos.
Chapter 1: The Nature of Statistics
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.
Copyright ©2011 Pearson Education 7-1 Chapter 7 Sampling and Sampling Distributions Statistics for Managers using Microsoft Excel 6 th Global Edition.
Agricultural and Biological Statistics. Sampling and Sampling Distributions Chapter 5.
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.
Sampling “Sampling is the process of choosing sample which is a group of people, items and objects. That are taken from population for measurement and.
Copyright © 2011 Pearson Education Information Gathering: Unobtrusive Methods Systems Analysis and Design, 8e Kendall & Kendall Global Edition 5.
IS 320 Systems Analysis and Design Notes for Textbook Chapter 5.
Information Gathering: Unobtrusive Methods Systems Analysis and Design, 7e Kendall & Kendall 5 © 2008 Pearson Prentice Hall.
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 1-1 Statistics for Managers Using Microsoft ® Excel 4 th Edition Chapter.
DTC Quantitative Methods Survey Research Design/Sampling (Mostly a hangover from Week 1…) Thursday 17 th January 2013.
Chapter 7 The Logic Of Sampling. Observation and Sampling Polls and other forms of social research rest on observations. The task of researchers is.
CHAPTER 4: SELECTING A SAMPLE Identify and describe four random sampling techniques. Select a random sample using a table of random numbers. Identify.
Tahir Mahmood Lecturer Department of Statistics. Outlines: E xplain the role of sampling in the research process D istinguish between probability and.
University of Sunderland Professionalism and Personal Skills Unit 9 Professionalism and Personal Skills Lecture Data Collection.
Learning Objectives Explain the role of sampling in the research process Distinguish between probability and nonprobability sampling Understand the factors.
7: Sampling Theory and Methods. 7-2 Copyright © 2008 by the McGraw-Hill Companies, Inc. All rights reserved. Hair/Wolfinbarger/Ortinau/Bush, Essentials.
3/5/2009Computer systems1 Information Gathering Unobtrusive methods: Sampling Investigation Observing a decision maker’s behavior Observing the physical.
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. 1 In an observational study, the researcher observes values of the response variable and explanatory.
Chapter 10 Sampling: Theories, Designs and Plans.
Bangor Transfer Abroad Programme Marketing Research SAMPLING (Zikmund, Chapter 12)
Lesson Sources of Errors in Sampling. Objectives Understand how error can be introduced during sampling.
7: The Logic of Sampling. Introduction Nobody can observe everything Critical to decide what to observe Sampling –Process of selecting observations Probability.
1-1 Copyright © 2014, 2011, and 2008 Pearson Education, Inc.
CHAPTER 34 Collection and Organisation of Data. PRIMARY AND SECONDARY DATA PRIMARY DATA is collected by an individual or organisation to use for a particular.
Sampling technique  It is a procedure where we select a group of subjects (a sample) for study from a larger group (a population)
Chapter 4 Sampling and Investigating Hard Data Systems Analysis and Design Kendall and Kendall Fifth Edition.
1 Data Collection and Sampling ST Methods of Collecting Data The reliability and accuracy of the data affect the validity of the results of a statistical.
Plan for Today: Chapter 1: Where Do Data Come From? Chapter 2: Samples, Good and Bad Chapter 3: What Do Samples Tell US? Chapter 4: Sample Surveys in the.
Consumer Behavior, Ninth Edition Schiffman & Kanuk Copyright 2007 by Prentice Hall Chapter 2 Consumer Research.
1 Market research. 2 Market research is the process of gathering and interpreting data about customers and competitors within a firm’s target market.
Fact Finding (Capturing Requirements) Systems Development.
Collecting Samples Chapter 2.3 – In Search of Good Data Mathematics of Data Management (Nelson) MDM 4U.
Lecture 5.  It is done to ensure the questions asked would generate the data that would answer the research questions n research objectives  The respondents.
Market research. Market research is the process of gathering and interpreting data about customers and competitors within an organisation’s target market.
Data Collection Techniques
Chapter 5 Information Gathering: Unobtrusive Methods
Collecting Data.
SAMPLING (Zikmund, Chapter 12.
Business and Management Research
Information Gathering: Unobtrusive Methods
Data Sampling Jerry Post Copyright © 1997
Week Three Review.
Business and Management Research
SAMPLING (Zikmund, Chapter 12).
Presentation transcript:

Chapter 4 Topics –Sampling –Hard data –Workflow analysis –Archival documents

Sampling A process of systematically selecting representative elements of a population A System analyst has to make a decision on 2 key issues: –Which of the key documents and Web sites should be sampled –Which people should be interviewed or sent questionnaires

Need for Sampling The reasons systems analysts do sampling are –Reduction of costs More time & cost involves to ask all employees, reading all web pages Redundant data –Speeding up the data-gathering process Little burden to gather sampled data rather than all data –Improving effectiveness Ask detail questions to few employees which requires little time and the analyst can follow up on missing and incomplete data –Reduction of data-gathering bias i.e. Biased interview by the executive who like to see the project successful

Sampling Design Steps To design a good sample, a systems analyst needs to follow four steps: –Determining the data to be collected or described Identify attributes, variable, associated data item Data gathering methods like interview, questionnaire, observation etc. –Determining the population to be sampled Duration of analysis (i.e. 2 month, 1 year) Determine whether interview should take place on one level or all level of organization or outside of the organization –Choosing the type of sample –Deciding on the sample size

Four Types of Sampling Convenience samples –System analyst post a notice asking everyone interested in new sales performance report to come to a meeting at 1 PM on 12 th December –Easiest to arrange but most unreliable Purposive samples –Analyst chooses group of knowledgeable individuals who are interested in the field –Moderately reliable

Four Types of Sampling (contd.) Simple Random Sampling –Based on a numbered list of the population –Each person or document has an equal chance of being selected –Choose every k-th element –Not always practical Complex Random Sampling –Has three forms Systematic sampling: –select every k-th element like simple random sampling Stratified sampling: –sub group the population (i.e. executive level, line level) & then sample Cluster sampling: –select a group of document or people to study –There are many “sonali” bank around the country. Investigate 1 or 2 of them

Sample Size Sample size depends on the cost as well time required by the system analyst Sample size under ideal condition is determined by: –Sampling data on attributes –Sampling data on variables –Sampling qualitative data

Steps to Determine Sample Size for Attribute Data –Determine the attribute to sample –Locate the database or reports where the attribute is found –Examine the attribute and estimate p, the proportion of the population having the attribute –Make the subjective decision regarding the acceptable interval estimate, i –Choose the confidence level and look up the confidence coefficient (z value) in a table –Calculate σ p, the standard error of the proportion as follows: i σ p = z

p(1-p) n = + 1 σ p 2 Steps to Determine Sample Size for Attribute Data (Contd.) –Determine the necessary sample size, n, using the following formula:

Confidence Level Table

Hard Data In addition to sampling, investigation of hard data is another effective method for systems analysts to gather information Hard data can be obtained by –Analyzing quantitative documents such as records used for decision making –Performance reports –Records –Data capture forms –E-commerce and other transactions

Workflow Analysis Workflow analysis may reveal signs of larger problems, such as Data or information doesn’t flow as intended –Too many or too few people, wrong people receiving it Bottlenecks in the processing of forms Access to online forms is cumbersome –e.i. Web forms must be printed and then sent rather than electronic submission Unnecessary duplication of work occurs because employees are unaware that information is already in existence on another form that they don’t know Employees lack understanding about the interrelatedness of information flow –e.i. they don’t know that their output works as input to another person

Archival Documents A systems analyst may obtain some valuable information by abstracting data from archival documents Generally, archival documents are historical data, and they are prepared and kept by someone else for specific purposes