LAW RESEARCH METHODOLOGY QUANTITATIVE RESEARCH

LAW RESEARCH METHODOLOGY QUANTITATIVE RESEARCH

Role Name Affiliation Principal Investigator Prof. (Dr.) Ranbir Singh Vice Chancellor, National Law University, Delhi Co-Principal Investigator Prof. (Dr.) G.S. Bajpai Registrar, National Law University Delhi Paper Coordinator Prof. (Dr.) G.S. Bajpai Registrar, National Law University Delhi Content Writer/Author Dr Manish Singh Dr RML National Law University, Lucknow Content Reviewer Prof. (Dr.) G.S. Bajpai Registrar, National Law University Delhi DESCRIPTION OF MODULE Items Subject Name Paper Name Module Name/Title Module Id Description of Module Law Research Methodology Quantitative Research IX Quantitative research is explaining phenomena by collecting numerical data that are analysed using mathematically based methods (in particular statistics). Aliaga and Gunderson (2000) Introduction When one thinks of quantitative methods, he/she probably have specific things in mind. He/she will probably be thinking of statistics, numbers, and may be feeling somewhat apprehensive because you think quantitative methods are difficult. Apart from the last one, all these thoughts capture some of the essence of quantitative methods. The aim is to understand the quantitative method of research, its meaning, its role, when do we do that and to understand its relationship with qualitative research. Learning Outcomes To understand the meaning and nature of quantitative research To understand its relationship with qualitative research To find out the similar themes between quantitative and qualitative research

To expose difference between qualitative and quantitative research. To understand the importance and meaning of it by way of an illustrative examples. To have a broad review of research analysis process. The Roadmap 1. What is Quantitative Research? 2. Dissecting the Definition of Quantitative Research. 3. When do we use quantitative methods? 4. Quantitative and Qualitative Research: The Relationship. 4.1 Difference in Research Design. 4.1.1 Difference in sampling. 4.1.2 Difference in the manner how the data is recorded. 4.1.3 Difference in data analysis. 4.1.4 Difference in their views and significance. 5. Quantitative Formulations Explained by Way of an Example. 6. Analyzing data. 6.1 Classify the data. 6.2 Analyze the data. 7. Conclusion. Suggested Readings Assessment / Evaluation 1. What is quantitative research? It is a systematic investigation of quantitative properties, their observable occurrence and relationship. It involves the use of methodological techniques that represent the human experience in numerical categories, sometimes referred to as statistics. Personal abilities and personality traits can be quantitative property. In quantitative research, the relationship between an independent and dependent variable in a

population is determined. Quantitative research method can be descriptive or experimental. In former quantitative research, subjects are usually measured once. A descriptive study establishes only associations between variables. In experimental quantitative research, subjects are measured before and after a treatment. An experimental research establishes causality. Quantitative research is designed to test hypotheses. Factors to be considered in assessing quantitative research designs include external validity, the construction of the sample, the presence of confounding factors, the appropriateness of the pool from which the sample is drawn, selection effects that may arise in forming a sample, the generalizability of the findings, the falsifiability of the hypothesis to be tested, and the replicability of the study. These factors center on whether or not the test conditions -- whether experimental, a survey, or an aggregate data set -- accurately mirror broader reality. This analysis will only produce valid results if the data are of high quality in the first place. 2. Dissecting the Definition of Quantitative Research. Remind yourself of the working definition given in the introduction. The first part of the definition is about explaining phenomena. This is the key essence of every research, be it quantitative or qualitative. We seek answers to phenomenons. In law, there could be questions like, what factors influence people to commit theft? Whether our prison system is reforming the prisoners or not?, and so on. The specificity of quantitative research lies in the second part of the definition. In quantitative research, we collect numerical data. This is closely connected to the last part of the definition: analysis using mathematically based methods. In order to be able to use mathematically based methods, our data have to be in numerical form. This is not the case for qualitative research. Therefore, as quantitative research is essentially about collecting numerical data to explain a particular phenomenon, particular questions seem immediately suited to being answered using quantitative methods. How many prisoners didn t displayed a recidivist tendency after serving their imprisonment? What was the time line in disposal of cases relating to rape against women?

3. When do we use quantitative methods? While taking a practical approach to research methods, the first question that we need to answer is what kind of questions are best answered by using quantitative as opposed to qualitative methods? There are four main types of research questions that quantitative research is particularly suited to finding an answer to: 1. One that demands a quantitative answer. Examples are: How many patents were granted to Indian MNC s post-2005 amendment in the Patents Act, 1970? or How many under trials are languishing in the jail for more than 10 years? That we need to use quantitative research to answer this kind of question is obvious. Qualitative, nonnumerical methods will obviously not provide the researcher with the numerical answer we want. 2. Numerical change can likewise accurately be studied only by using quantitative methods. Are the numbers of students joining the schools has improved due to education policy and legal reforms? The researcher needs to undertake a quantitative study to find out. 3. In order to find out about the state of something or other, the researcher often wants to explain phenomena. What factors predict the judicial outcomes? What factors are related to pendency of cases in the courts? These kinds of question can also be studied successfully by quantitative methods, and many statistical techniques have been developed that allow us to predict scores on one factor, or variable from scores on one or more other factors, or variables. 4. Quantitative research is especially suited is the testing of hypotheses. We might want to explain something for example, whether there is a relationship between convicts and their self-esteem and social background. We could look at the theory and come up with the hypothesis that weaker social economic background leads to low self-esteem, which would in turn be related to the tendency to commit crime. 4. Quantitative and Qualitative Research: The Relationship

Conversely qualitative research provides detailed description and analysis of the quality, or the substance of the human experience. They share some commonalities both in theory and practice. They cannot be called exactly diametrically opposite. Both quantitative and qualitative research is both build on the empirical methods to decipher the workings of social, cultural, and legal processes. They differ, however, in how they go about this deciphering. Regardless of methodological experiences and theoretical differences, both agree that social research should be based on the real world: interviews, interactions, documents, observations etc in the social world. Where philosophy givers may contemplate the very existence of world, researchers would accept that there is a social reality worthy of investigation. They also share the belief that the scientific inquiry shall be logical and consistent. Thus, both of them requires systematic adherence to certain rules and procedures. The quantitative-qualitative distinction can also be criticized from the utilitarian perspective. In fact, rather than being tied to a particular method or techniques it can be replaced with a more practical approach of using what works. So the goal is not about deciding right from wrong but it is in fact to choose an approach that is suitable for the task at hand. Methods are but tools for doing research. For example, if one is interested in comparing the number of suicide committed by men and women in the year 2013, we should use numerical data. But if we have to study this tendency vis-àvis their capacity to cope with this news about death of their loved ones, it might be more practical to gather descriptive data. 4.1 Differences in Research Designs The design is the series of steps the researcher would take from the beginning to the end of his research. These include: 1. Asking a research question based on a theory 2. Selection of respondents and data collection 3. Analysis of data 4. Reporting the results. They all follow this steps but the order in which they are followed and their interdependence varies from qualitative to quantitative research.

4.1.1 Difference in Sampling In quantitative research, one of the first steps in conducting a quantitative research is the selection of respondents or participants. The precondition of statistical analysis requires that respondents be selected randomly. This process is referred to as sampling. The people and objects selected from a specified population is known as a sample. The sample should be large and representative, reason being that small size increases the probability of biased results or error. In qualitative research, it is less technical and more about theoretical considerations. Sampling techniques in qualitative research are purposive, meaning that the theoretical purpose of the research mandates the selection process and not the strict methodological mandate. While studying about drug peddlers random sampling is impossible, purposive approach therefore is the only option. 4.1.2 Difference in manner how the data is recorded Quantitative researchers quantify their observations using a pre-coded form referred to as a survey. However, not every study can be done that way because it can have many complexities. Say for example if we have to study motor accidents, it might be the case that the cause of accident might be intoxication which was pre coded as one, or may be driver was minor which was pre coded as two. Now what if it is both the causes would be marked as just one? or just two? or both? That s the problem a researcher might face so it becomes necessary to narrate a brief description of the accident on the basis of the account of the victim, onlookers, police reports. So therein might be a case where it has to be further described using qualitative methods. 4.1.3 Difference in data analysis The data analysis in quantitative research is based on statistics using a formula based approach. It is an ever expanding and diverse field. And can involve, analyzing one variable at a time, exploring the relationship between two variables or testing relationships among various variables. In comparison qualitative approach, it is less formula based but rather more emphasis is laid on the context, social or cultural. 4.1.4 Difference in their views and significance The quantitative research is by and large detached from methods. It introduces a theory initially in order to establish the rationale of their research and returns to it at

the end of the research in order to advance the policy implications. The concerns are phrased in statistical or numerical terms. The qualitative differs in the sense that it tends to focus upon the quid pro quo of the theory and methods. So it is theoretically more rigorous and much lesser statistical as compared to quantitative research. 1 5. Quantitative Formulation Explained by Way of an Example The example is entirely hypothetical and does not intend to reflect the true state of law. There can be factors which the court shall consider in order to decide a case. Like for example in a dispute concerning copyright infringement, the defence of fair use is taken. Then the court has to consider the nature and scope of the copyrighted work, the originality of the work, the amount of copying, economic injury to the copyright owner. Assuming these are the only 4 controlling circumstances. Assume, furthermore, that four cases already have been decided. In Case 1, all four circumstances were present, and the decision was in favor of the party seeking redress. In Case 2, circumstances 1 and 2 were present, and the decision again was in favor of the aggrieved party. But in Case 3, circumstances 1 and 3 were present, and the decision was against the party seeking redress. In case 4 where circumstances 2 nd 3 were present was decided in the favour of party seeking redress. What decision can be expected on that basis in a case in which circumstances 3 and 4 are present? Neither the stated rule of law that circumstances 1, 2, 3 and 4 shall be controlling for the decision, nor any of the decisions which already have been reached, offers an answer to this question. If it can be assumed, however, that the available decisions as well as future decisions form a consistent pattern of judicial action, a mathematical model can be designed which provides an answer to this very question. In the proposed model, each case will be treated as an equation, in which the decision is a function of the combination of the controlling circumstances in the case. Accordingly, the circumstances of the case are the independent variables in the equation, and the decision is the dependent variable. In this fashion, the cases which already have been 1 See Marvasti, Amir B., Qualitative Research in Sociology, SAGE Pub. 2004 at p. 9-12.

decided provide a set of simultaneous equations, in which the weights of the controlling circumstances are the unknowns. By solving these equations, a weight is found for each of the controlling circumstances, and by substituting these weights in the equation which represents a new case, a numerical index for the particular combination of circumstances and for the corresponding decision is obtained. Moreover, since the weights of the controlling circumstances now are known, a numerical index for any combination of circumstances and for its corresponding decision can be determined. (an adaptation from Lawlor) 6. Analyzing Data Data can assume many shapes and forms. The role of analysis is to bring data together in a meaningful way and enable the researcher and the audience to interpret it. The steps are as following: 2 6.1 Classify the data Before analyzing the data it is essential to classify/code it in some way. This is the method of preparing the data for analysis. It is organizing the data to analyze it. Example, converting the responses in a questionnaire form and coding them in numeric forms. The analysis depends on the data type. For example, the number of juvenile offenders involved in violent crimes every year in relation to a particular offence would be a qualitative data. The coding frame is dependent on the amount of data the researcher is having and the requirement of the audience. If it is concerned with details, more categories are required, and if it is a broad overview, lesser categories would be needed. 6.2 Analyzing the data The data can be analyzed on a descriptive basis, that is, to describe the data. It may also be an analysis that questions the data or tests hypothesis. It is inferential analysis and involves subjecting the data to a statistical analysis. As far as descriptive analysis 2 See David Wilkinson (ed.), Analyzing Data in The Researcher s Toolkit, Routledge, (2000) at p. 77-96

is concerned, a researcher shall be mindful about the knowledge of their audience. Variables are one of the factors in the data. For example, age, gender etc. might be variables. A variable can either be dependent or independent. A dependent variable is one that would change following an increase or decrease in an independent variable. For example the exam results can be a dependent variable in contrast with the number of lectures attended, an independent variable. The data can be presented in numbers on a graph, or in the form of percentages. This type of analysis provides a description of the data which can be easily read as it is reduced from the mass and have been split upon the basis of various factors. It can be a tally chart however, it can further be conveniently reduced to groups say age groups that uses a five year category. 16 17 25 35 36 22 32 17 19 21 32 42 47 41 35 21 48 32 30 20 22 19 22 32 35 36 34 35 31 32 Figure1: Age of offenders in auto burglary in 2013. The figure 2 below is in the tally form Age 16 17 19 20 21 22 25 Number of offenders 1 2 1 1 1 1 1 Age 30 31 32 34 35 36 41 42 Number of offenders 1 1 4 1 4 2 1 1 Age 47 48 Number of offenders 1 1 Age 15-20 21-25 26-30 31-35 36-40 41-45 46-50 Number of Offenders 4 3 1 10 2 2 2 Figure 3: On the basis of age groups. The above 3 figures suggest that the figure 3 is more informative in answering as to which age group was found to be most involved in auto theft as compared to figure 1 and 2. The Mode, Median and Mean

The Mode of a group of data is the most frequently occurring value. The median is the value that separates the upper half of a list of values from the lower half. The mean is the average. That is sum of total values divided by the number of values. They are all measures of what is known as central tendency. One which best describes the group. Standard Deviation It is a tool to measure dispersion. It shows the relation a set of value has to the mean. Associating Data Some of the researcher s data would require him to explore relationship between two different set of variables. This is also known as correlation research. There are numerous methods for doing that, but the two most popular methods are Spearman s rank order correlation coefficient and Pearson s product movement correlation coefficient. Inferential Analysis It assists the researcher in making conclusions about the data by performing certain operations on it. With inferential analysis the researcher is inferring from his sample data what the population scores are. Sample is a selection taken from a group. It can be called to be the representation of that group. As a result the findings of the sample can be generalized back to the group. The population is a group who share the same characteristics. The major difference between differential analysis and inferential analysis is that the researcher in the former aims to describe the data while in latter he aims at making conclusions about it. 7. Conclusion The qualitative research as explained above can give meaningful insights and suggestions to the information that is scattered everywhere. It gives us concrete results and indications by performing statistical analysis by converting the information into numerical formulas. The quantitative research has its own merits visa-vis qualitative research.