UNIT I Structure UNDERSTANDING QUANTITATIVE RESEARCH Kiran Prasad Understanding Quantitative Research 1.1 Introduction 1.2 Objectives 1.3 Foregrounding Quantitative Research 1.4 Concepts and Constructs 1.5 Variables 1.6 Measurements 1.7 Scales and Indices 1.8 Reliability and Validity of Measurement 1.9 Quantitative/Quallitative Research 1.10 Limitations of Quantitative Research 1.11 Let Us Sum Up 1.12 Glossary 1.13 Unit End Questions 1.14 References 1.15 Suggested Readings 1.1 INTRODUCTION We have studied what is research in Block 1. The concepts, methods and procedures of qualitative research have been explained in Block 2. In this Block we will study quantitative research which is used widely in social sciences such as sociology, anthropology, political science, and gender studies. In the social sciences, quantitative research refers to a systematic and empirical study of quantitative properties and phenomena and their relationships. In this Unit we are going to look at various aspects and concepts that we need to understand before proceeding with how to conduct quantitative research. The Unit begins with building our understanding of what is quantitative research, what are the core concepts and constructs that shape this type of research. The next section discusses what do we understand by variables, measurements, scales and indexes. Reliability and reliability of the measurement is explained followed by what are the limitations of quantitative research. Let us now have a look at your expected knowledge building after reading this unit. 199
Quantitative Research 1.2 OBJECTIVES After studying this unit, you will be able to: Describe different types of variables; Explain the various levels of measurement; Understand reliability and validity of measurement; Discuss quantitative research methods; and Analyse the limitations of quantitative research. 1.3 FOREGROUNDING QUANTITATIVE RESEARCH Quantitative research can be done using primary or secondary data. Primary data is gathered by a researcher directly from the respondents in a research study. Secondary data is data collected by some one other than the researcher who is the using it at that point of time. It is also available in macro data sets such as the Census and national databases. Macro data sets ( explained in Unit 4 of this Block) can also be used to conduct a research study. In many research studies, secondary data are used to supplement and support primary data that are collected by a researcher. For example, in a study of land ownership among women in a State or district, data can be collected from a group of women selected for study which forms the primary data in the study. Land registration records available in revenue offices are the secondary data that are available to the researcher to support the primary data that is gathered from these women. Box No. 1.1 Sources of data Primary source is an original object or document, first hand information gathered from historical, legal documents, eye witness account, results of experiments, statistical data, pieces of creative writing and art objects. In social sciences, primary data are often empirical studies- research where direct observation is made. A secondary source is something written about a primary source, includes comments on, interpretations of or discussion about original material. 200 The objective of quantitative research is to develop and use mathematical models, theories and/or hypotheses pertaining to various phenomena. The three basic elements of quantitative research - concepts and constructs, variables; and measurement are defined and discussed in the following sections. It is important to understand these elements before we proceed to understand and conduct quantitative research.
1.4 CONCEPTS AND CONSTRUCTS Understanding Quantitative Research According to Kerlinger, (1973) concept is a term that expresses an abstract idea formed by generalization from particulars. It is formed by summarizing related observations. For example, the word house is a concept that represents a wide variety of observable objects, ranging from four walls supported by thatched roof or tiles, to a dwelling place made up of a concrete structure. In Women s and Gender Studies, terms such as gender, empowerment and feminism are used as concepts. Concepts help to facilitate communication among those who share an understanding of them. Concepts can be used by researchers to make meaningful summaries of observations. These summaries help researchers to organize their observations and data and to look for explanations or patterns in them. Whereas a construct is a combination of concepts that are difficult to observe directly, but can be inferred from related behaviour patterns. For example, in Gender Studies, patriarchy is a attribute that is specifically defined to describe the state of social thinking which is determined by concepts such as superiority of men, submission of women, exploitation of women and violence against women. Patriarchy cannot be seen but its presence can be determined by a questionnaire or standardized test. Box No.1.2 Concepts and constructs are used in quantitative research to explain abstract observations in a measurable form such as a questionnaire or standardized test. Let us now look at some of the important concepts in quantitative research. 1.5 VARIABLE A variable in quantitative research, is a phenomenon or event that can be measured or manipulated. It is an entity that can take on different values. Researchers attempt to test a number of associated variables to develop an underlying meaning or relationship among them. For example, education is one of the variables that is used to study the status of women. Types of Variables Variables can be classified in terms of their relationship with each other. In quantitative research the aim of a study is to determine the relationship between an independent variable and a dependent or outcome variable in a population. Independent variables can be varied by the researcher. For example, independent variables like income, education and occupation fall into various categories which is used by a researcher to explain its effect on the status of women which is a dependent variable. 201
Quantitative Research The value of a dependent variable depends on the effects or changes in the independent variables. The values of the independent variable can not be manipulated and are only observed or measured. In other words, the dependent variable is what the researcher wishes to explain. For example, women s educational status is the dependent variable that depends on independent variables like family income, parent s education and parent s occupation. Thus, the researcher wishes to explain women s educational status, is a dependent variable which will vary according to family income, parent s education and parent s occupation. Box No. 1.3 We must keep in mind that the distinction between the types of variable depend on the purpose of the research study. An independent variable in one study may be a dependent variable in another study. For example, a study to determine Effect of Women s Education on Age at Marriage would have women s education as the independent variable and age at marriage as the dependent variable. But the age at marriage will be an independent variable in a study to determine Reproductive Health of Women in a Community and number of children born is a dependent variable. Two forms of variables are used in social research. They are discrete and continuous variables. A discrete variable includes a finite set of values; it cannot be divided into sub parts. For example, the number of female students in a class is a discrete variable because the unit is a person. It would not make sense to say that there are 2.25 female students in a class because we cannot conceptualize 0.25 of a person. Population, sex and religious affiliation are other discrete variables. A continuous variable can take on any value including fractions and be meaningfully broken into subparts. For example, we can measure the height of persons using decimal places like 131.5 cm or 135.2 cm. The time spent by women on household tasks can be expressed as 1.30 hours on cleaning, 1.15 hours on washing, 2.25 hours on cooking etc. Here, we can talk of 0.15 hours or 0.25 hours meaningfully. Variables are also defined as quantitative and qualitative variables. Quantitative variables are those that can be expressed in terms of numbers or quantity. For example, height, weight and age are expressed in terms of numbers. Qualitative variables are those variables that are expressed in terms of attributes or qualities. For example, the colour of the eyes (black, brown, grey, green), the satisfaction of women with the health services (satisfied or dissatisfied) are expressed in terms of descriptive attributes or qualities. 202
1.6 MEASUREMENT Understanding Quantitative Research The process of measurement is central to quantitative research. Quantitative research requires that the variables under consideration can be measured. It provides the fundamental connection between empirical observation and mathematical expression of quantitative relationships. In simple terms, in measurement, the researcher assigns numerals to objects, events or properties according to certain rules. For example, unemployment increased by 5%. The female literacy rate was 54% as estimated in 2001 Census. It is relatively easy to measure properties like height, weight, or time than attributes like beauty, friendship or choosing a religion which are abstract. There are four different levels of measurement: nominal, ordinal, interval, and ratio. The nominal level is the least powerful form of measurement. In this measurement, numerals or other symbols are used to classify persons, objects, or characteristics. For example, matter can be classified into three categories: solid, liquid and gas. A researcher who assigns 1 to solid, 2 to liquid and 3 to gas has formed a nominal scale. The numerals assigned are simply labels that stand for the respective categories and they have no mathematical significance. The nominal level has the basic property of equivalence. If an object is placed in category 1, it is considered equal to all other objects in that category. An example of nominal measurement in the area of gender studies would be classifying women according to the nature of their employment. Those who are employed in government and private enterprises would be in category 1, those who are self-employed would be in category 2 and those who are unemployed would be placed in category 3. Nominal scales are widely used in research to assign data to different categories. The ordinal level is used to classify and arrange persons, objects, or characteristics according to ranks. Ranks are used to place persons, objects, or characteristics in order, but the distance between two objects on a scale are not equal. Ordinal scales are used only for ranking from the highest to the lowest. For example, athletes running in various events such as 100m, 200m and 500m are arranged according to their positions first, second, third and so on. An example of ordinal measurement in the area of gender studies would be ranking of women in athletics. In this case, we can only say that an athlete is higher or lower on the scale and it is not possible to make more accurate comparisons. We can only state whether the ranking is faster than or slower than without being able to state how fast or slow. 203
Quantitative Research An interval scale has intervals between adjacent points that are of equal value. For example, in an interval scale the same degree of heat is needed to heat an object from 40 to 50 degrees as to heat it from 50 to 60 degrees. The disadvantage of the interval scale is that it lacks a true zero point. This means that the researcher cannot make statements of a proportional nature; for example, someone with an IQ of 100 is not twice as intelligent as someone with an IQ of 50. The interval level of measurement is frequently used in gender studies to measure attitudes towards social values by measuring response like agree, disagree or undecided. Scales at the ratio level of measurement have all the properties of interval scales with the true zero point. With this fixed zero point, ratio judgments can be made. For example, time, distance, height and weight are ratio measures. We can say in ratio scale that a car traveling at 50 kilometers an hour is going twice as fast as a car traveling at 25 kilometers an hour. Box No. 1.4 While nominal level is only concerned with classification, the ordinal level has the properties of ranking in addition to classification. The interval scale has all the properties of the ordinal level in addition to intervals between adjacent points on a scale with equal value. The ratio scale has the additional property of a true zero point. It is important to assess your understanding from the sections that you have read till now. Check Your Progress: i) What are the different kind of variables?. ii) Distinguish between a dependent and an independent variable. iii) Enumerate upon different levels of measurement. 204
In the next section you will read about scales and indices and their significance in quantitative research. Understanding Quantitative Research 1.7 SCALES AND INDICES Quantitative data analysis requires construction of two types of measures of variables- scales and indices. Some measures like the number of women in population of a State can be adequately measured without scales and indices. The measurement of gender equality is complex and requires the use of specially developed scales and indices. A scale is a measurement of intensity of an attitude and emotions. Indices are a measure of quantity of some social phenomenon and are constructed at ratio level of measurement. Scales and Indices are both ordinal measures of variables. Scales and indices represent composite measures of variables or measurements that are based on more than one item. They are used to measure complex variables which cannot be measured using a single item or single indicator. Multiple items and indicators are assembled into one composite value to develop a scale. Scales: The most commonly used scale to study social attitudes is the Likert scale. A number of statements are made with respect to a topic. Respondents can strongly agree, agree, be neutral, disagree or strongly disagree with the statements. Each response is weighted and all the responses of a subject are added to produce a single score on the topic. An example of Likert Scale is given below: 1) Women police officers should be appointed in all police stations in the interest of women : Score Assigned strongly agree 5 agree 4 neutral 3 disagree 2 strongly disagree 1 This is an example of a positive item and the weightage of the score that can be given to the responses. 205
Quantitative Research 2) Having women police officers in all police stations does not serve the interests of women: Score Assigned strongly agree 1 agree 2 neutral 3 disagree 4 strongly disagree 5 This is an example of a negative item. In a negatively worded item scores are reversed to maintain attitude consistency. There are some limitations of the Likert scale. That is that there is always a chance that people have answered according to the general thinking than how they feel about an issue. This scale can only tell us the differences in attitudes between respondents but cannot tell us the degree of differences between people who respond to the same attitude scale. Nevertheless, the Likert scale is relatively easy to construct and frequently used in measurement of attitudes. Another widely used scaling procedure is the semantic differential scale. This general technique for measuring the meaning of an item was developed by Charles E. Osgood, G. J. Suci and P. H. Tannenbaum (Osgood et al., 1957). In this scale, the name of a concept is placed at the top a series of points, by which the respondent rates the concept through bipolar adjectives used to measure attitudes. For example, a scale of this technique can be used to measure attitudes to the Women s Era magazine. Women s Era magazine Good Bad Biased Unbiased Valuable Worthless The bipolar adjectives to measure attitudes toward Women s Era magazine are good/bad, biased/unbiased, valuable/worthless and so on. Each measurement must have a unique set of bipolar objectives. Indices: 206 The potential advantage of an index is that it provides a good summary of a complex multidimensional problem like gender equality. An index measuring gender equality can help to understand the complexities of gender relations, and facilitate comparisons across time and countries. The first global indices designed to reflect gender disparities were the Gender-related Development
Index (GDI) and Gender Empowerment Measure (GEM) that were formulated in the 1995 Human Development Report. Understanding Quantitative Research The GDI was developed to measure gender inequalities in an overall assessment of well-being measured by the Human Development Index (HDI). It is a composite measure of well-being comprising achievements in health, education and incomes. HDI is low if gender inequality exists in any of the three dimensions. Thus, GDI is also a measure of a given country s level of human development. The GEM was introduced as a complementary measure of gender equality in political, economic and decision making power. The three dimensions included are (i) control over economic resources, measured by men and women s earned income; (ii) economic participation and decision making, measured by women and men s share of administrative, professional, managerial, and technical positions; and (iii) political participation and decision making, measured by male and female shares of parliamentary seats. GEM gives an evaluation of some aspects of female empowerment. The Gender Inequality Index (GII) focuses on educational attainment, economic and political participation, and reproductive health issues and inequalities at the national level. The Gender Inequality Index is designed to capture women s disadvantage in three dimensions - empowerment, economic activity and reproductive health - for as many countries as possible. The GII shows the loss in human development due to inequality between female and male achievements in these dimensions. The various indices that are important in understanding quantitative research will be further explained in Unit-4 of this Block. 1.8 RELIABILITY AND VALIDITY OF MEASUREMENT All scales are tested to ensure reliability and validity of measurement before being used in research. A measurement must have these two related qualities to be useful in research. Reliability: The general meaning of reliability holds good in research also. A reliable person is one whose behaviour will be dependable, consistent and stable unlike an unreliable person. Similarly, measurements should be reliable so that we can trust the values or scores. A measurement is reliable if it consistently gives the same answer at different points in time. For example, a scale used to measure the length of a table must give the same score if used repeatedly at different points of time. Validity: In addition to being reliable, a measurement must also be valid. If a measuring device measures what it is supposed to measure, the device is a valid one. To assess validity the researcher must use his or her judgement. 207
Quantitative Research For example, to weigh an object one will use a weighing scale, not a scale that measures length. To give you another example, it is possible to validate a test of entrepreneurial skills in women by administering a test to a group of women who run small businesses and a group of women who do not engage in any such activity. The test is valid as it measures the entrepreneurial skills of women who are running small businesses among a group of such women. The items of this test will not yield the same responses among a group of women who do not run small businesses. Attempt the following exercise to assess your learning from the last section. Check Your Progress: i) What is reliability of measurement? ii) What is validity of measurement? iii) What type of data (nominal, ordinal, interval or ratio) does each type of measurement represent? Students of Humanities and Sciences List of top sportswomen A scale measuring weight over time A scale measuring attitudes towards women s equality 208 Frequency of married and unmarried women
1.9 QUALITATIVE / QUANTITATIVE RESEARCH Understanding Quantitative Research While quantitative research relates to empirical methods which are based on facts and figures, used to analyze and explain a phenomena while qualitative research is used to explain the reasons for such trends. Qualitative research is useful in social and behavioural sciences including Women s and Gender Studies, to understand the various factors that influence human behaviour. Qualitative research is also useful to understand the history of the women s movement, the role of society in shaping women s identities and the perceptions on status of women. Let us now look at the table given below to understand some of the differences between the two types of researches. S.No. Quantitative Research Qualitative Research 1 Based on numbers, applying Based on words to present analysis measurement procedures to social life 2 Projects researcher s point of view Projects participant s point of view 3 Test a theory Emergence of theory 4 Structured Unstructured 5. Makes generalizations Provides contextual understanding 6. Concrete, reliable data Rich, deep data 7. Takes place in artificial settings Takes place in natural settings Adapted from: Bryman, 2008, p.393 Hardy and Bryman (cited in Bryman, 2008, p.294) have pointed out that though there are clear differences in the two types of researches, but there are meaningful similarities too. Let us have a look at the similarities in the way both qualitative and quantitative research are carried out. 1) Data sifting: Large quantity of data is collected and then reduced to the amount to make sense. 2) Aims at addressing the research questions: The nature of research questions is different but the primary endeavour is to project nature of social reality. 3) Relate data analysis to existent literature: Both answers gaps in available literature on the issue of research, though the methodology is totally different. 4) Use appropriate methods to investigatethe research questions: Selection of methods and approaches to analyse the data should be suitable to the research questions. 209
Quantitative Research 1.10 LIMITATIONS OF QUANTITATIVE RESEARCH The quantitative research methods may be inappropriate in many areas of life such as forming friendships, love and marriage, choosing a religion and evaluating works of art, which are based on subjective experiences (Kerlinger, 1973). There are many crucial qualitative elements of empowerment, but quantitative measures for all attributes do not exist. For example, female and male labour force participation rates are used in measuring economic activity. However, much of women s work, especially in the home and in family businesses, is unpaid, and that women s informal work is not measured. Thus, labour force participation does not accurately reflect the unpaid work of women. Similarly, violence against women, both inside and outside the home, is an important issue, but it is not measured with consistency in quantitative data. Many quantitative studies only deal with acts of physical violence against women; emotional violence against women is hard to quantify and measure. General insecurity - including unrest and strife in society- can also pose a risk to women s physical safety as well as their participation in society, but there is not much quantitative data on these dimensions. Then, there is another limitation that measurement process rely on understanding of reality as an outsider by the researcher whereas the participants/ respondents may have a different understanding of a particular phenomenon.. Like in the above example, violence against women is not treated that way by the victims themselves as it has been defined by the researcher. In urban slums of Delhi, women accept acts of physical violence as punishment for their wrong doing and emotional violence in not known to be exiting for them. Quantitative research also over looks case specific variations as it needs sufficient numbers to generalize. 1.11 LET US SUM UP This unit describes concepts and constructs, different types of variables, the various levels of measurement, scales and indices, reliability and validity of measurement, quantitative research methods and the limitations of quantitative research. There are different types of variables such as quantitative, qualitative, discrete, continuous, and dependent; and independent variables. There are four levels of measurements: nominal, ordinal, interval and ratio. To be useful in research, measurements must be valid and reliable. An understanding of all of the above is helpful in understanding quantitative research. 210
Quantitative research relates to empirical methods which are based on facts and figures. Concepts can be used by researchers to make meaningful summaries of observations. A construct is a combination of concepts that are difficult to observe directly, but can be inferred from related behaviour patterns. Understanding Quantitative Research A variable is a phenomenon or event that can be measured or manipulated and is used in quantitative research. The values of the dependent variable depend on the effects or changes in the independent variables. The values of the independent variable are not manipulated and are only observed or measured. The dependent variable is what the researcher wishes to explain. Scales and indices represent composite measures of variables or measurements that are based on more than one item. All scales are tested to ensure reliability and validity of measurement before being used in research. A measurement is reliable if it consistently gives the same answer at different points in time. If a measuring device measures what it is supposed to measure the device is a valid one. Quantitative and qualitative research have differences and similarities in many ways that govern the methodology and outcome of research. 1.12 GLOSSARY Quantitative : A description or analysis of a phenomenon that involves Research specific measurement of variables. Variable : A phenomenon or event that is measured or manipulated in research. Reliability : A measurement that consistently gives the same answer at different points in time. Validity : A measurement that measures what it is supposed to measure. 1.12 UNIT END QUESTIONS 1) What is quantitative research? Describe the basic elements of quantitative research. 2) Explain with examples the different types of variables in research. 3) Describe the various levels of measurement of data. 4) Explain how scales and indexes are useful in quantitative research. 5) What is reliability and validity of measurement? Discuss with the help of examples. 211
Quantitative Research 1.13 REFERENCES Babbie, Earl (2010). The Practice of Social Research 2 nd Edition. Belmont C A: Wadsworth Bryman, Alan (2008). Social Research Methods. New York: Oxford University Press. Goode, William and Hatt Paul, K. (1952). Methods in Social Research. New York: Mc Graw Hill. Kerlinger, F. (1973). Foundations of Behavioural Research (2 nd edition). New York: Holt, Reinhart and Winston. Kothari, C.R. (2004). Research Methodology Methods and Techniques 2 nd Edition. New Delhi: New Age International (P) Limited. Osgood, Charles E., G. J. Suci and P. H. Tannenbaum (1957). The Measurement of Meaning. Urbana: University of Illinois Press. 1.15 SUGGESTED READINGS Bryman, Alan (2008). Social Research Methods. New York: Oxford University Press. Kothari, C.R. (2004). Research Methodology Methods and Techniques 2 nd Edition. New Delhi: New Age International (P) Limited. Singh, Kultar (2007). Quantitative Social Research Methods. New Delhi: Sage. 212