1 Module Detail and its Structure Subject Name Sociology Paper Name Methodology of Research in Sociology Module Name/Title Processing and Analyzing Quantitative Data Module Id RMS 20 Pre-requisites Some knowledge on social statistics Objectives This module will deal with the issues involved in the process of handling, managing and interpreting quantitative data collected in the process of research. It will also discuss about the basic statistical tools with the help of which we analyse social phenomena. Keywords Coding, editing, statistics, quantitative research, measures of central tendency, dispersion, coefficient correlation and regression. Role in Content Name Affiliation Development Principal Investigator Prof. Sujata Patel Dept. of Sociology, University of Hyderabad Paper Co-ordinator Prof. Biswajit Ghosh Professor, Department of Sociology, The University of Burdwan, Burdwan 713104 Email: [email protected] Ph. M +91 9002769014 Content Writer Dr. Udita Mitra Assistant Professor, Department of Sociology, Shri Shikshayatan College, Kolkata-700095 Email: [email protected] Ph. M +91 9433213816 Ph. L (O) 033-24140594 Content Reviewer (CR) Prof. Biswajit Ghosh Professor, Department of Sociology, The & Language Editor University of Burdwan, Burdwan 713104 Name of Paper: Methodology of Research in Sociology Sociology Name of Module: Processing and Analyzing Quantitative Data 2 Contents 1. Objective .................................................................................................................................... 3 2. Introduction…………………………………………………………………………………….3 3. Learning Outcome .................................................................... Error! Bookmark not defined. 4. Data Processing ........................................................................ Error! Bookmark not defined. 4.1 Editing ........................................................................................................................................ 3 4.2 Coding……………………………………………………………………………………….....3 4.3 Classification .............................................................................................................................. 4 4.4. Tabulation..................................................................................................................................4 Self-check exercise – 1..............................................................................................................4 5. Data Analysis…………………………………………………………………………………..5 6. Statistics in Social Research…………………………………………………………………...5 Self-check exercise – 2..............................................................................................................6 6.1 Measures of Central tendency .................................................................................................... 6 6.2 Measures of Dispersion ............................................................................................................ ..9 6.3 Chi-Square Test ........................................................................................................................ 13 6.4 T-test.......................................................................................................................................15 6.5 Measures of Relationship…………………………………………………………………….18 Self-check Exercise - 3…………………………………………………………………….....22 7. Limitations of Statistics in Sociology…………………………………………………………23 8. Summary..................................................................................................................................23 9. References ................................................................................................................................ 25 Name of Paper: Methodology of Research in Sociology Sociology Name of Module: Processing and Analyzing Quantitative Data 3 1. Objective This module will deal with the issues involved in the process of handling, managing and interpreting quantitative data collected in the process of research. It will also discuss about the basic statistical tools with the help of which we analyse social phenomena. 2. Introduction Quantitative research can be construed as a research strategy that emphasizes quantification in the collection and analysis of data. It entails a deductive approach to the relationship between theory and research in which the accent is placed on testing the theories. Quantitative research usually incorporates the practices and norms of the natural scientific model and of positivism in particular and it also embodies a view of social reality as an external, objective reality (Bryman 2004: 19). It also has a preoccupation with measurement and involves a process of collecting large amount of data. These data may be collected through various ways like survey and field research. The data, after collection, have to be processed in order to ensure their proper analysis and interpretation. According to Kothari (2004), technically, processing implies editing, coding, classification and tabulation of collected data so that they are amenable to analysis. These endeavours help us to search for patterns of relationship that exist among data-groups (Ibid.: 122). 3. Learning Outcome This module will help you to understand different issues involved in processing and analysing quantitative data. It will also help you to grasp the essential steps of applying various statistical measures in order to interpret data collected through social research. 4. Data Processing Data reduction or processing mainly involves various steps necessary for preparing the data for analysis. These steps involve editing, categorising the open-ended questions, coding, computerization and preparation of tables (Ahuja 2007: 304). The processing of data is an essential step before analysis because it enables us to overcome the errors at the stage of data collection. 4.1. Editing According to Majumdar (2005), error can come in at any stage of social research especially in the stage of data collection. These errors have to be kept at a minimum level to avoid errors in the results of the research. Editing or checking for errors in the completed questionnaires is a laborious exercise and needs to be done meticulously. Interviewers tend to commit mistakes like some questions are missed out; some answers remain unrecorded or are recorded at the wrong places. The questionnaires therefore need to be checked for completeness, accuracy and uniformity (Ibid.: 310). 4.2. Coding Coding implicates the process of assigning numbers or other symbols to answers so that they can be categorized into specific classes. Such classes should be appropriate to the research problem under consideration (Kothari 2004: 123). Careful consideration should be made so as not to leave out any response uncoded. According to Majumdar (2005: 313), a set of categories is referred to as “coding frame” or “code book”. Code book explains how to assign numerical codes for response categories Name of Paper: Methodology of Research in Sociology Sociology Name of Module: Processing and Analyzing Quantitative Data 4 received in the questionnaire/schedule. It also indicates the location of a variable on computer cards. Ahuja (2007: 306) provides an example to illustrate how variables can be coded. In a question regarding the religion of the respondent the answer categories of Hindu, Muslim, Sikh, and Christian can be coded as 1, 2, 3, and 4 respectively. In such cases, the counting of frequencies will not be according to Hindus, Muslims etc., but as 1, 2 and so on. Coding can be done manually or with the help of computers. 4.3. Classification Besides editing and coding of data, classification is another important method to process data. Classification has been defined as the process of arranging data into groups and classes on the basis of some common characteristics (Kothari 2004: 123). Classification can be of two types, namely Classification according to attributes or common characteristics like gender, literacy etc., and Classification according to class intervals whereby the entire range of data is divided into a number of classes or class intervals. 4.4. Tabulation Tabulation is the process of summarising raw data and displaying the same in compact form for further analysis (Kothari 2004: 127). The necessity of tabulating raw data is: It conserves space and reduces explanatory and descriptive statement to a minimum, and It provides a basis for various statistical computations. Tabulation can be done manually as well as with electronic and mechanical devices like computers. When the data are not large in number, tabulation can be done by hand with the help of tally marks. Self check exercise – 1 Question 1. Tabulate the following examination grades for 80 students. 72, 49, 81, 52, 31,38,81, 58,68, 73, 43, 56, 45, 54, 40, 81, 60, 52, 52, 38, 79, 83, 63, 58, 59, 71, 89, 73, 77, 60, 65, 60, 69, 88, 75, 59, 52, 75, 70, 93, 90, 62, 91, 61, 53, 83, 32, 49, 39, 57, 39, 28, 67, 74, 61, 42, 39, 76, 68, 65, 58, 49, 72, 29, 70, 56, 48, 60, 36, 79, 72, 65, 40, 49, 37, 63, 72, 58, 62, 46 (Levin and Fox 2006). Procedures for Tabulation/Grouping of Data The above is an array of scores which otherwise would not be very handy to use. In order to make the data meaningful and useful it must be organized and classified into frequency tables. There are certain easy steps to be followed in order to convert the raw scores into frequency tables. i. We must first find the difference between the highest and the lowest score