DOCSLIB.ORG

Processing of Data and Analysis

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Processing of Data and Analysis Conceptual Paper Biostatistics and Epidemiology International Journal Processing of data and analysis Dr Balkishan Sharma Sri Aurobindo Medical College & PG Institute, India Correspondence: Dr Balkishan Sharma, PhD, Associate Professor (Biostatistics), Department of Community Medicine, Sri Aurobindo Medical College & PG Institute, Indore (MP), India, Email [email protected] and [email protected] Received: February 06, 2018 | Published: February 20, 2018 Copyright© 2018 Sharma. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Introduction Health research is essential in developing evidence-based interventions Data-processing techniques that will make a difference in mitigating health problems, promoting health and ultimately improving the quality of life. Data collected Once the fieldwork has been completed, the information that has been and compiled from experimental work, records and surveys should gathered must be centralized and input to the computer. Data entry is be accurate and complete. They must be checked for accuracy tiresome work, but it isnecessary to accord it some attention because and adequacy before processing further. So far they lie in masses, of inevitable errors in reading and entering the information, especially are scattered in the records and in other words they are mixed and if it is not carried out by people accustomed to using a keyboard for unsorted. data-entry. The computerized data can be stored in tabular form in a spreadsheet (e.g. Microsoft Excel, Lotus 123) or more compactly and The processing of data and further analysis may be break up into efficiently in a relational database management system (e.g. Access, three stages: (1) data management, (2) explanatory data analysis Oracle, dBase). and (3) statistical analysis (testing and modeling). However, before proceeding for statistical analysis, researcher must consider the Methods of statistical processing following raised points: Statistics offers a range of methods, the choice of which will depend ✓ Understand the process involved in data processing. on four factors: (1) The type of variables: qualitative or quantitative; (2) The status of the variables: explanatory or dependent; (3) The ✓ Use computers to perform data processing. number of variables: one, two or multiple and (4) the type of analysis: ✓ Distinguish between qualitative and quantitative data. exploratory (descriptive) or confirmatory (inferential). ✓ Understand probabilities and their applications. Scope and purpose ✓ Interpret summary statistics, graphical presentation and Data analysis is the process of developing answers to questions contingency tables. through the examination and interpretation of data. The basic steps ✓ Commonly presented in the health literature. in the analytic process consist of identifying issues, determining the availability of suitable data, deciding on which methods are ✓ Carry out exploratory data analysis. appropriate for answering the questions of interest, applying the methods and evaluating, summarizing and communicating the results. ✓ Understand the process involved in estimations and hypothesis testing. Analytical results underscore the usefulness of data sources by shedding light on relevant issues. Data analysis also plays a key role ✓ Interpret the functions of confidence intervals and p-values. in data quality assessment by pointing to data quality problems in a ✓ Understand statements in published articles relating to statistics. given survey. Analysis can thus influence future improvements to the survey process. ✓ Use computers to perform some statistical analysis. Exploratory data analysis involves examination of the data errors and Quality indicators describing data using summary statistics and graphical techniques Main quality elements: relevance, interpretability, accuracy, (descriptive statistics). As data errors are often detected at this accessibility. An analytical product is relevant if there is an audience stage, the process of exploratory data analysis and data cleaning are who is (or will be) interested in the results of the study. For the typically iterative. The aim of this process is, for the researcher to gain interpretability of an analytical article to be high, the style of writing familiarity with, and understanding of the data, in order to determine must suit the intended audience. Sufficient and relevant details must the approach to take, and methods to use in further statistical analyzes. Submit your Article | www.ologypress.com/submit-article Citation: Sharma B. Processing of data and analysis. Biostatistics Epidemiol Int J. (2018);1(1): 3-5. Ology Press DOI: 10.30881/beij.00003 Biostatistics and Epidemiology International Journal 4 be provided so that another person if allowed access to the data could ✓ Distinguishing data types. replicate the results. ✓ Distinguishing different types of Statistical tests. For an analytical product to be accurate, appropriate methods and ✓ Identify the selection of a right test. tools need to be used to produce the results. For an analytical product to be accessible, it must be available to people for whom the research ✓ Determining statistical significance. results would be useful. ✓ Distinguishing between Parametric and Non-Parametric test Analysis of data with their applying criteria. Data analysis converts data into information and knowledge, and ✓ Distinguishing between Correlation and Regression. explores the relationship between variables. Data Analysis is the ✓ Drawing unbiased inference. process of systematically applying statistical and/or logical techniques to describe and illustrate, condense and recap, and evaluate data. ✓ Inappropriate subgroup analysis. According to Shamoo & Resnik1 various analytic procedures “provide ✓ Lack of clearly defined and objective outcome measurements. a way of drawing inductive inferences from data and distinguishing the signal (the phenomenon of interest) from the noise (statistical ✓ Partitioning ‘text’ when analyzing qualitative data. fluctuations) present in the data.” ✓ Reliability and Validity. Understanding of the data analysis procedures will enable you to ✓ appreciate the meaning of the scientific method which includes Extent of analysis. testing of hypotheses and statistical significance in relation to Table 1 consists of common statistical tests. All tests which are research questions. There are a number of issues that researchers described below are provided in the book titled Intuitive Biostatistics should be cognizant of with respect to data analysis. Some of the key by Harvey Motulsky2 and were performed by InStat, except for tests considerations in analysis and selection of the right test of significance marked with asterisks. Tests labeled with a single asterisk are briefly are as follows: mentioned in this book, and tests labeled with two asterisks were not mentioned at all. ✓ Having the necessary skills to analyze. Table 1 Common statistical tests Type of Data Rank, Score, or Measurement Binomial Goal Measurement (from (from Non-Gaussian (Two Possible Survival Time Gaussian Population) Population) Outcomes) Kaplan Meier survival Describe one group Mean, SD Median, Interquartile range Proportion curve Compare one group to Chi-square or Binomial One-sample t test Wilcoxon test - a hypothetical value test** Compare two unpaired Fisher's test (chi-square Log-rank test or Mantel- Unpaired t test Mann-Whitney test groups for large samples) Haenszel* Compare two paired Conditional proportional Paired t test Wilcoxon test McNemar's test groups hazards regression* Compare three or Cox proportional hazard more unmatched One-way ANOVA Kruskal-Wallis test Chi-square test regression** groups Compare three or Repeated-measures Conditional proportional Friedman test Cochrane Q** more matched groups ANOVA hazards regression** Rank, Score, or Measurement Binomial Measurement (from Goal (from Non-Gaussian (Two Possible Survival Time Gaussian Population) Population) Outcomes) Submit your Article | www.ologypress.com/submit-article Citation: Sharma B. Processing of data and analysis. Biostatistics Epidemiol Int J. (2018);1(1): 3-5. DOI: 10.30881/beij.00003 Ology Press 5 Biostatistics and Epidemiology International Journal (Table 1 continuous..) Quantify association Contingency Pearson correlation Spearman Correlation - between two variables Coefficients** Predict value from Cox proportional hazard another measured Simple LR or Non LR Nonparametric Regression** Simple Logistic regression* variable Regression* Predict value from Multiple LR* or Multiple Multiple Logistic Cox proportional hazard several measured or - Non LR** Regression* regression* binomial variables *briefly mentioned in Intuitive Biostatistics2 **not mentioned in Intuitive Biostatistics2 Developments in the field of statistical data analysis often parallel 5. http://www.emacpd.org/sites/default/files/resource_center/3.Data%20 or follow advancements in other fields to which statistical methods Processing%20Module.pdf are fruitfully applied. Data is known to be crude information and not 6. Korn EL, Graubard BI. Analysis of health surveys. John Wiley & Sons. knowledge by itself. The sequence from data to knowledge is: from 2011;323. Data to Information, from Information to Facts, and finally, from Facts to Verification of Truth. Data becomes information, when it becomes 7. Lehtonen
Load more

Recommended publications
  • Comparison Between Census Software Packages in the Context of Data Dissemination Prepared by Devinfo Support Group (DSG) and UN Statistics Division (DESA/UNSD)
    Comparison between Census software packages in the context of data dissemination Prepared by DevInfo Support Group (DSG) and UN Statistics Division (DESA/UNSD) For more information or comments please contact: [email protected] CsPro (Census and Survey Redatam (REtrieval of DATa for CensusInfo DevInfo* SPSS SAS Application Characteristics Processing System) small Areas by Microcomputer) License Owned by UN, distributed royalty-free to Owned by UN, distributed royalty-free to CSPro is in the public domain. It is Version free of charge for Download Properitery license Properitery license all end-users all end-users available at no cost and may be freely distributed. It is available for download at www.census.gov/ipc/www/cspro DATABASE MANAGEMENT Type of data Aggregated data. Aggregated data. Individual data. Individual data. Individual and aggregated data. Individual and aggregated data. Data processing Easily handles data disaggregated by Easily handles data disaggregated by CSPro lets you create, modify, and run Using Process module allows processing It allows entering primary data, define It lets you interact with your data using geographical area and subgroups. geographical area and subgroups. data entry, batch editing, and tabulation data with programs written in Redatam variables and perform statistical data integrated tools for data entry, applications command language or limited Assisstants processing computation, editing, and retrieval. Data consistency checks Yes, Database administration application Yes, Database administration
    [Show full text]
  • Research; *Electronic Data Processing; Information Processing; Information Systems; *Manpower Utilization; *Personnel Data; Personnel Management; Questionnaires
    DOCUMENT RESUME ED 084 382 CE 000 533 AUTHOR Bayhylle, J. E., Ed.; Hersleb, A., Ed. TITLE The Development of Electronic Data Processing in Manpower Areas; A Comparative Study of Personnel Information Systems and their Implications in Six European Countries. INSTITUTION Organisation for Economic Cooperation and Development, Paris (France) . PUB DATE 73 NOTE 366p. AVAILABLE FROMOECD Publications Center, Suite 1207, 1750 Pennsylvania Ave., N.W., Washington, DC 20006 ($8.50) EDRS PRICE MF-$0.65 HC- $13.16 DESCRIPTORS Case Studies; Data Bases; Data Processing; *Ecqnomic .Research; *Electronic Data Processing; Information Processing; Information Systems; *Manpower Utilization; *Personnel Data; Personnel Management; Questionnaires ABSTRACT Usable data about human resources in the ecqnqmy are fundamentally important, but present methods of obtaining, organizing, and using such information are increasingly unsatisfactory. The application of electronic data processing to manpower and social concerns should be improved and increased. This could stimulate closer exchange between government, institutions, and business enterprises in the collection and dissemination of manpower data. The first phase of the study was a broad-scope questionnaire of 38 companies in Austria, France, Germany, Great Britain, Sweden, and Switzerland which have developed, or are planning to develop, computer-based personnel information, systems. The second phase consisted of depth study of eight of the companies. Case study investigations were concerned with the content and function of the system and with the administrative and personnel consequences of the introduction of such systems. A set of key.points which emerged from the study is developed. A model demonstrates the need for coordination to increase communication vertically and horizontally.
    [Show full text]
  • Applied Accounting and Automatic Data-Processing Systems." (1962)
    Louisiana State University LSU Digital Commons LSU Historical Dissertations and Theses Graduate School 1962 Applied Accounting and Automatic Data- Processing Systems. William Elwood Swyers Louisiana State University and Agricultural & Mechanical College Follow this and additional works at: https://digitalcommons.lsu.edu/gradschool_disstheses Recommended Citation Swyers, William Elwood, "Applied Accounting and Automatic Data-Processing Systems." (1962). LSU Historical Dissertations and Theses. 745. https://digitalcommons.lsu.edu/gradschool_disstheses/745 This Dissertation is brought to you for free and open access by the Graduate School at LSU Digital Commons. It has been accepted for inclusion in LSU Historical Dissertations and Theses by an authorized administrator of LSU Digital Commons. For more information, please contact [email protected]. This dissertation has been 62—3671 microfilmed exactly as received SWYERS, William Elwood, 1922- APPLIED ACCOUNTING AND AUTOMATIC DATA-PRO CESSING SYSTEMS. Louisiana State University, Ph.D., 1962 Economics, commerce—business University Microfilms, Inc., Ann Arbor, Michigan APPLIED ACCOUNTING AND AUTOMATIC DATA-PROCESSING SYSTEMS A Dissertation Submitted to the Graduate Faculty of the Louisiana State University and Agricultural and Mechanical College in partial fulfillment of the requirements for the degree of Doctor of Philosophy in The Department of Accounting by William Eiu<Swyers B.S., Centenary College, 1942 M.B.A. t Louisiana State University, 1948 January, 1962 ACKNOWLEDGMENTS The writer wishes to express appreciation to Dr. Robert H. Van Voorhis, Professor of Accounting, Louisiana State University, for his valuable assistance and guidance in the preparation of this dissertation. The writer wishes to acknowledge, also, the helpful suggestions made by Dr. W. D. Ross, Dean of the College of Business Administration, Dr.
    [Show full text]
  • STANDARDS and GUIDELINES for STATISTICAL SURVEYS September 2006
    OFFICE OF MANAGEMENT AND BUDGET STANDARDS AND GUIDELINES FOR STATISTICAL SURVEYS September 2006 Table of Contents LIST OF STANDARDS FOR STATISTICAL SURVEYS ....................................................... i INTRODUCTION......................................................................................................................... 1 SECTION 1 DEVELOPMENT OF CONCEPTS, METHODS, AND DESIGN .................. 5 Section 1.1 Survey Planning..................................................................................................... 5 Section 1.2 Survey Design........................................................................................................ 7 Section 1.3 Survey Response Rates.......................................................................................... 8 Section 1.4 Pretesting Survey Systems..................................................................................... 9 SECTION 2 COLLECTION OF DATA................................................................................... 9 Section 2.1 Developing Sampling Frames................................................................................ 9 Section 2.2 Required Notifications to Potential Survey Respondents.................................... 10 Section 2.3 Data Collection Methodology.............................................................................. 11 SECTION 3 PROCESSING AND EDITING OF DATA...................................................... 13 Section 3.1 Data Editing ........................................................................................................
    [Show full text]
  • What Can a Computer Do? a Computer Is an Electronic Device
    You have learnt various methods of data processing and representation that you can use to analyse the geographical phenomena in the preceding chapters. You must have observed that these methods are time consuming and tedious. Have you ever thought of a method of data processing and their graphical representation that can save time and improve efficiency? If you have used a computer for word processing, then you must have noticed that the computer is more versatile as it facilitates the onscreen editing of the text, copy and move it from one place to another, or even delete the unwanted text. Similarly, the computer may also be used for data processing, preparation of diagrams/graphs and drawing of maps, provided you have an access to the related application software. In other words, a computer can be used for a wide range of applications. It must, however, be clearly understood that a computer carries out the instructions it receives from the users. In other words, it cannot perform any function on its own. In the present chapter, we will discuss the use of computers in data processing and mapping. What can a Computer do? A computer is an electronic device. It consists of various sub-systems, like memory, micro-processor, input system and output system. All these sub- systems work together to make it an integrated system. It is an extremely powerful device, which is apt to have an important effect on the systems of data processing, mapping and analysis. A computer is a fast and a versatile machine that can perform simple arithmetic operations, such as, addition, subtraction, multiplication and division, and can also solve complex mathematical, formulae.
    [Show full text]
  • 14. Data Processing, Evaluation, and Analysis
    In: R.P. Higgins & H. 'I'hi,el (Eds.) Introduction to the study of Meiofauna. ~vashington and London', Sml't11sonian Institution Press, 1988, pp. 197-231. Communication no. 418 Delta Institute for Hydrobiological Research, Vierstraat 28 Yerseke, The Netherlands. 14. Data Processing, Evaluation, and Analysis Carlo Heip, Peter M.J. Herman, and Karlien Soetaert This chapter aims at introducing a number of and evenness indices in part 5, and temporal pattern methods for the post-hoc interpretation of field in part 6. Each of these topics is discussed data. In many ecological studies a vast amount of independently and each topic can be consulted information is gathered, often in the form of without having to read the others. For this reason, numbers of different species. The processing of these each part will be preceded by its own introduction. data is possible on different levels of sophistication and requires the use of tools varying from pencil Part 1. Data Storage and Retrieval and paper to a mini computer. However, some "number crunching" is nearly always necessary and The existence of many software packages, useful with the increasing availability and decreasing prices in ecology, will not be unknown to most ecologists. ,of the personal computer, even in developing Many computer centers provide their users with countries, there is little point in avoiding the more routines which facilitate the input, transformation and advanced statistical techniques. There is also a more appropriate output of the data, and the linking of fundamental reason: ecological data are often of a available software packages into one flexible system.
    [Show full text]
  • Course Title: Fundermentals of Data Processing
    NATIONAL OPEN UNIVERSITY OF NIGERIA SCHOOL OF EDUCATION COURSE CODE: BED 212: COURSE TITLE: FUNDERMENTALS OF DATA PROCESSING BED 212: FUNDERMENTALS OF DATA PROCESSING COURSE DEVELOPER & WRITER: DR. OPATEYE JOHNSON AYODELE School of Education National Open University of Nigeria 14/16 Ahmadu Bello Way, Victoria Island Lagos. Nigeria. COURSE CORDINATOR: DR. INEGBEDION, JULIET O. School of Education National Open University of Nigeria 14/16 Ahmadu Bello Way, Victoria Island Lagos. Nigeria. INTRODUCTION BED 212: FUNDERMENTALS OF DATA PROCESSING This course is designed to equip the students with knowledge of the data processing in technical and vocational education (TVE) especially Business Education research. WHAT YOU WILL LEARN You will learn the components of data processing, hardware and software components, file management and organization in Business Education- based data. It will also interest you to learn about basics of research, approaches and designs with data gathering techniques. Relevant statistical tools you can use to analyse your data would be across and how to write your research reports. COURSE AIMS This course aims at producing competent business educators who will be versed in organizational and research data processing in order to foster time and effective information that will be used in decision making. In order to enable you meet the above aims, modules constituting of units have been produced for your study. Apart from meeting the aims of the course as a whole, each course unit consists of learning objectives which are intended to ensure your learning effectiveness. COURSE OBJECTIVES The course objectives are meant to enable you achieve/acquire the following: 1) Gain in-depth knowledge of data processing and its functions in business organisations and educational settings.
    [Show full text]
  • Hyperspectral Data Processing. Algorithm Design and Analysis
    Brochure More information from http://www.researchandmarkets.com/reports/2293144/ Hyperspectral Data Processing. Algorithm Design and Analysis Description: Hyperspectral Data Processing: Algorithm Design and Analysis is a culmination of the research conducted in the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, Baltimore County. Specifically, it treats hyperspectral image processing and hyperspectral signal processing as separate subjects in two different categories. Most materials covered in this book can be used in conjunction with the author’s first book, Hyperspectral Imaging: Techniques for Spectral Detection and Classification, without much overlap. Many results in this book are either new or have not been explored, presented, or published in the public domain. These include various aspects of endmember extraction, unsupervised linear spectral mixture analysis, hyperspectral information compression, hyperspectral signal coding and characterization, as well as applications to conceal target detection, multispectral imaging, and magnetic resonance imaging. Hyperspectral Data Processing contains eight major sections: - Part I: provides fundamentals of hyperspectral data processing - Part II: offers various algorithm designs for endmember extraction - Part III: derives theory for supervised linear spectral mixture analysis - Part IV: designs unsupervised methods for hyperspectral image analysis - Part V: explores new concepts on hyperspectral information compression - Parts VI & VII: develops
    [Show full text]
  • Cit 213 Course Title: Elementary Data Processing
    NATIONAL OP EN UNIVERSITY OF NIGERIA SCHOOL OF SCIENCE AND TECHNOLOGY COURSE CODE: CIT 213 COURSE TITLE: ELEMENTARY DATA PROCESSING CO URSE GUIDE CIT 213 ELEMENTARY DATA PROCESSING Course Developer Dr. Ikhu-Omoregbe N. A. Course Editor Course Co-ordinator Afolorunso, A. A. National Open University of Nigeria Lagos. NATIONAL OPEN UNIVERSITY OF NIGERIA National Open University of Nigeria Headquarters 14/16 Ahmadu Bello Way Victoria Island Lagos Abuja Annex 245 Samuel Adesujo Ademulegun Street Central Business District Opposite Arewa Suites Abuja e-mail: [email protected] URL: www.nou.edu.ng National Open University of Nigeria 2008 First Printed 2008 ISBN All Rights Reserved Printed by .. For National Open University of Nigeria TABLE OF CONTENTS PAGE Introduction.............................................................................. 1 - 2 What you will learn in this Course..................................... 2 Course Aims............................................................................... 2 Course Objectives...................................................................... 2 3 Working through this Course.................................................... 3 Course Materials...........................................................................3 Study Units ............................................................................... 3 - 4 Textbooks and References ........................................................ 4 - 5 Assignment File.......................................................................
    [Show full text]
  • Data Processing Operations Technician
    Fremont Unified School District Classified Job Description Office and Technical DATA PROCESSING OPERATIONS TECHNICIAN DEFINITION Under general supervision, assists in the day-to-day operation of the Management Information Systems Department; assists users with centralized MIS and/or help desk requests; operates electronic computer and peripheral equipment; and performs related work as assigned. CLASS CHARACTERISTICS This class provides a variety of technical assistance to the Management Information Systems Department, in the areas of tracking and processing mainframe operations jobs and in providing technical assistance to users in various District offices and school sites. This class is distinguished from Computer Operator/Programmer in that the latter performs programming activities in addition to batch and on-line operations within the MIS centralized operations center. EXAMPLES OF DUTIES Receives users requests; determines the appropriate staff to fulfill the request and processes required paperwork; refers special requests to programmers or other technical staff. Schedules batch jobs, ensures and tracks proper sequence to meet established deadlines and user needs. Operates the mainframe console and peripheral equipment to run batch jobs and/or initiates command files for later execution. Obtains printouts of reports to be distributed. Loads appropriate forms and paper styles on line printers. Prepares tapes for microfiche or other long-term storage; calls for pick-up, files and distributes when returned. Maintains database elements, ensuring continuing validity. Assists Operations Supervisor in evaluating operation of the computer and related equipment and in maintaining the system communication scheme. Provides information and assistance to system-users, facilitating on-line applications. In event of malfunction, resets the current operation or contacts appropriate District or vendor support staff as required.
    [Show full text]
  • An Analysis of Information Technology on Data Processing by Using Cobit Framework
    (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 6, No. 9, 2015 An Analysis of Information Technology on Data Processing by using Cobit Framework Surni Erniwati Nina Kurnia Hikmawati Academy of Information Management and Computer Telkom University Bandung AMIKOM Mataram Universitas Telkom Bandung Mataram, Indonesia Bandung, Indonesian Abstract—Information technology and processes is inter administrative services and academic information quickly and connected, directing and controlling the company in achieving accurately. ABASA already supported by IT in data corporate goals through value-added and balancing the risks and processing, which for the procurement of IT is implemented by benefits of information technology. This study is aimed to analyze a separate division, namely division BPSI. However, research the level of maturity (maturity level) on the data process and has not been done to measure the maturity level data produced information technology recommendations that can be processing and mapping the information technology process made as regards the management of IT to support the academic maturity level of the institution cannot be measured, in addition performance of the service to be better. Maturity level to these problems relating to data processing, how to maintain calculation was done by analyzing questionnaires on the state of the completeness, accuracy and availability of data through the information technology. The results of this study obtainable that efforts of data backup, data storage or deletion of data. Based the governance of information technology in data processing in Mataram ASM currently quite good. Current maturity value for on those problems, this study is aimed to make a the data processing has the value 2.69.
    [Show full text]
  • Processing the Data
    CHAPTER 7 PROCESSING THE DATA This chapter is written for survey coordinators, data processing experts and technical resource persons. It provides information on how to: Prepare for processing the data Set up a system for managing data processing Carry out data entry Edit the data and create a ‘clean’ data file for analysis Produce tabulations with the indicators Archive and distribute data The MICS3 data-processing system is designed to deliver the first results of a survey within a few weeks after the end of fieldwork. This chapter contains information that will help you to undertake the planning and advance preparation that will make this goal a reality. The chapter begins by giving you an overview of the MICS3 data-processing system. It then discusses each of its components in detail, providing references to supplemental sources of information where appropriate. It closes with a set of three checklists that will help you make the processing of your survey data a success. OVERVIEW The reason that the MICS3 data-processing system can achieve such rapid turnaround time is because data is processed in tandem with survey fieldwork. Data for each cluster is stored in a separate data file and is processed as soon as the questionnaires are returned from the field. This approach breaks data processing down into discrete segments and allows it to progress while fieldwork is ongoing. Thus, by the time the last questionnaires are finished and returned to headquarters, most of the data have already been processed. Processing the data by clusters is not difficult, but it does require meticulous organization.
    [Show full text]