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reserach in social sciences
In sociology, quantitative research refers to the systematic empirical investigation of social phenomena via statistical, mathematical or numerical data or computational techniques.[1] The objective of quantitative research is to develop and employ mathematical models, theories and/or hypotheses pertaining to phenomena. The process of measurement is central to quantitative research because it provides the fundamental connection between empirical observation and mathematical expression of quantitative relationships. Quantitative data is any data that is in numerical form such as statistics, percentages, etc.[1] In layman's terms, this means that the quantitative researcher asks a specific, narrow question and collects a sample of numerical data from participants to answer the question. The researcher analyzes the data with the help of statistics. The researcher is hoping the numbers will yield an unbiased result that can be generalized to some larger population. Qualitative research, on the other hand, asks broad questions and collects word data from participants. The researcher looks for themes and describes the information in themes and patterns exclusive to that set of participants.
More generally, quantitative research is widely used in social sciences such as psychology, economics, sociology, marketing, community health, health & human development, gender and political science, and less frequently in anthropology and history. Research in mathematical sciences such as physics is also 'quantitative' by definition, though this use of the term differs in context. In the social sciences, the term relates to empirical methods, originating in both philosophical positivism and the history of statistics, which contrast with qualitative research methods.
Qualitative methods produce information only on the particular cases studied, and any more general conclusions are only hypotheses. Quantitative methods can be used to verify which of such hypotheses are true.
A comprehensive analysis of 1274 articles published in the top two American sociology journals between 1935 and 2005 found that roughly two thirds of these articles used quantitative methods.[2]
Contents
[hide]
Overview[edit]
Quantitative research is generally made using scientific methods, which can include:
The generation of models, theories and hypotheses
The development of instruments and methods for measurement
Experimental control and manipulation of variables
Collection of empirical data
Modeling and analysis of data
Quantitative research is often contrasted with qualitative research, which is the examination, analysis and interpretation of observations for the purpose of discovering underlying meanings and patterns of relationships, including classifications of types of phenomena and entities, in a manner that does not involve mathematical models.[3] Approaches to quantitative psychology were first modeled on quantitative approaches in the physical sciences by Gustav Fechner in his work on psychophysics, which built on the work of Ernst Heinrich Weber. Although a distinction is commonly drawn between qualitative and quantitative aspects of scientific investigation, it has been argued that the two go hand in hand. For example, based on analysis of the history of science, Kuhn concludes that “large amounts of qualitative work have usually been prerequisite to fruitful quantification in the physical sciences”.[4] Qualitative research is often used to gain a general sense of phenomena and to form theories that can be tested using further quantitative research. For instance, in the social sciences qualitative research methods are often used to gain better understanding of such things as intentionality (from the speech response of the researchee) and meaning (why did this person/group say something and what did it mean to them?) (Kieron Yeoman).
Although quantitative investigation of the world has existed since people first began to record events or objects that had been counted, the modern idea of quantitative processes have their roots in Auguste Comte's positivist framework.[5]Positivism emphasized the use of the scientific method through observation to empirically test hypotheses explaining and predicting what, where, why, how, and when phenomena occurred. Positivist scholars like Comte believed only scientific methods rather than previous spiritual explanations for human behavior could advance.
Use of statistics[edit]
Statistics is the most widely used branch of mathematics in quantitative research outside of the physical sciences, and also finds applications within the physical sciences, such as in statistical mechanics. Statistical methods are used extensively within fields such as economics, social sciences and biology. Quantitative research using statistical methods starts with the collection of data, based on the hypothesis or theory. Usually a big sample of data is collected – this would require verification, validation and recording before the analysis can take place. Software packages such as SPSS and R are typically used for this purpose. Causal relationships are studied by manipulating factors thought to influence the phenomena of interest while controlling other variables relevant to the experimental outcomes. In the field of health, for example, researchers might measure and study the relationship between dietary intake and measurable physiological effects such as weight loss, controlling for other key variables such as exercise. Quantitatively based opinion surveys are widely used in the media, with statistics such as the proportion of respondents in favor of a position commonly reported. In opinion surveys, respondents are asked a set of structured questions and their responses are tabulated. In the field of climate science, researchers compile and compare statistics such as temperature or atmospheric concentrations of carbon dioxide.
Empirical relationships and associations are also frequently studied by using some form of General linear model, non-linear model, or by using factor analysis. A fundamental principle in quantitative research is that correlation does not imply causation, although some such as Clive Granger suggest that a series of correlations can imply a degree of causality. This principle follows from the fact that it is always possible a spurious relationship exists for variables between which covariance is found in some degree. Associations may be examined between any combination of continuous and categorical variables using methods of statistics.
Relationship with qualitative methods[edit]
In most physical and biological sciences, the use of either quantitative or qualitative methods is uncontroversial, and each is used when appropriate. In the social sciences, particularly in sociology, social anthropology and psychology, the use of one or other type of method can be a matter of controversy and even ideology, with particular schools of thought within each discipline favouring one type of method and pouring scorn on to the other. The majority tendency throughout the history of social science, however, is to use eclectic approaches-by combining both methods. Qualitative methods might be used to understand the meaning of the conclusions produced by quantitative methods. Using quantitative methods, it is possible to give precise and testable expression to qualitative ideas. This combination of quantitative and qualitative data gathering is often referred to as mixed-methods research.[8]
Example
Research that consists of the percentage amounts of all the elements that make up Earth's atmosphere.
Survey that concludes that the average patient has to wait two hours in the waiting room of a certain doctor before being selected.
An experiment in which group x was given two tablets of Aspirin a day and Group y was given two tablets of a placebo a day where each participant is randomly assigned to one or other of the groups. The numerical factors such as two tablets, percent of elements and the time of waiting make the situations and results quantitative.
In finance, quantitative research into the stock markets is used to develop models to price complex trades, and develop algorithms to exploit investment hypotheses, as seen in quantitative hedge funds and Trading Strategy Indices.

Qualitative research is a method of inquiry employed in many different academic disciplines, traditionally in the social sciences, but also in market research and further contexts.[1] Qualitative researchers aim to gather an in-depth understanding of human behavior and the reasons that govern such behavior. The qualitative method investigates the why and how of decision making, not justwhat, where, when. Hence, smaller but focused samples are more often used than large samples.
In the conventional view, qualitative methods produce information only on the particular cases studied, and any more general conclusions are only propositions (informed assertions). Quantitative methods can then be used to seek empirical support for such research hypotheses.

Data collection
Qualitative researchers face many choices related to data collection ranging from grounded theory practice, narratology, storytelling, classical ethnography, or shadowing. Qualitative methods are also loosely present in other methodological approaches, such as action research or actor-network theory. The most common method is the qualitative research interview, but forms of the data collected can also include group discussions, observation and reflection field notes, various texts, pictures, and other materials.[2]
Qualitative research often categorizes data into patterns as the primary basis for organizing and reporting results.[citation needed] Qualitative researchers typically rely on the following methods for gathering information: Participant Observation, Non-participant Observation, Field Notes, Reflexive Journals, Structured Interview, Semi-structured Interview, Unstructured Interview, and Analysis of documents and materials.[3]
The ways of participating and observing can vary widely from setting to setting. Participant observation is a strategy of reflexive learning, not a single method of observing.[4] In participant observation[5] researchers typically become members of a culture, group, or setting, and adopt roles to conform to that setting. In doing so, the aim is for the researcher to gain a closer insight into the culture's practices, motivations and emotions. It is argued that the researchers' ability to understand the experiences of the culture may be inhibited if they observe without participating[citation needed].
The data that is obtained is streamlined to a definite theme or pattern. This is further worked on and alternative research hypothesis is generated which finally provides the basis of the research statement.
Some distinctive qualitative methods are the use of focus groups and key informant interviews. The focus group technique involves a moderator facilitating a small group discussion between selected individuals on a particular topic. This is a particularly popular method in market research and testing new initiatives with users/workers.
In fields that study households, a much debated topic is whether interviews should be conducted individually or collectively (e.g. as couple interviews).[6][7]
One traditional and specialized form of qualitative research is called cognitive testing or pilot testing which is used in the development of quantitative survey items. Survey items are piloted on study participants to test the reliability and validity of the items.
There are several different research approaches, or research designs, that qualitative researchers use.[8] [9] In the academic social sciences, the most frequently used qualitative research approaches include the following:
1. Basic/generic/pragmatic qualitative research, which involves using an eclectic approach taken up to best match the research question at hand.
2. Ethnographic Research, . This method is also called "ethnomethodology" or "methodology of the people". An example of applied ethnographic research is the study of a particular culture and their understanding of the role of a particular disease in their cultural framework.
3. Grounded Theory is an inductive type of research, based or "grounded" in the observations or data from which it was developed; it uses a variety of data sources, including quantitative data, review of records, interviews, observation and surveys.
4. Phenomenology describes the "subjective reality" of an event, as perceived by the study population; it is the study of a phenomenon.
5. Philosophical Research is conducted by field experts within the boundaries of a specific field of study or profession, the best qualified individual in any field of study to use an intellectual analysis, in order to clarify definitions, identify ethics, or make a value judgment concerning an issue in their field of study their lives.
6. Critical Social Research, used by a researcher to understand how people communicate and develop symbolic meanings.
7. Ethical Inquiry, an intellectual analysis of ethical problems. It includes the study of ethics as related to obligation, rights, duty, right and wrong, choice etc.
8. Foundational Research, examines the foundations for a science, analyzes the beliefs, and develops ways to specify how a knowledge base should change in light of new information.
9. Historical Research allows one to discuss past and present events in the context of the present condition, and allows one to reflect and provide possible answers to current issues and problems. Historical research helps us in answering questions such as: Where have we come from, where are we, who are we now and where are we going?

In other fields[edit]
Positivism in the social sciences is usually characterized by quantitative approaches and the proposition of quasi-absolute laws. A significant exception to this trend is represented by cultural anthropology, which tends naturally towardqualitative approaches.[10]
In psychology the positivist movement was influential in the development of behavioralism and operationalism. The 1927 philosophy of science book The Logic of Modern Physics in particular, which was originally intended for physicists, coined the term operational definition, which went on to dominate psychological method for the whole century.[18]
Positivist Methodology in Social Sciences
The use of positivism as a research method in the social sciences dates back to August Comte, who wanted to institute a methodology based on facts rather than speculation. For Comte, the social sciences should deal with scientific laws instead of contemplation (Marcuse, 1941, p. 345). This "scientific method" continues to be the dominant method of conducting research in the social sciences. This paper argues that though positivism has contributed to the development of "value-free" social science and sociology. The first part of this paper examines positivism's contributions to social science research. These contributions include creating rules of research that continue to be followed today. The positivist research method has allowed sociologists to study the nature and structure of social organizations like the family, social class and political groups. Positivism has further led to the development of statistical research, which has given the social sciences a firmer analytical ground. However, this paper also argues that positivism has several important shortcomings. First, positivism is only concerned with observable phenomenon and misses nuanced effects that are not readily observable.
Positivism
Some sociologists have tried to adopt the methods of the natural sciences. In doing so, they have tended to advocate the use of quantitative methods. To use such methods in sociology is known as positivism. First, as a positivist, Comte believed that the scientific study of society should be confined to collecting information about phenomena that can be objectively observed and classified. Comte argued they sociologists should not be concerned with the internal meanings, motives, feelings and emotions of individuals. Since these mental states exist only in the person’s consciousness, they cannot be observed and so they cannot be measured in any objective way. The second aspect of positivism concerns its use of statistical data. Positivists believed it was possible to classify the social world in an objective way. Using these classifications it was then possible to count sets of observable social facts and so produce statistics. For example, Durkheim collected data on social facts such as the suicide rate and the membership of different religions. The third stage of positivist methodology entails looking for correlations between different social facts. A correlation is a tendency for two or more things to be found together, and it may refer to the strength of the relationship between them. In his study of suicide, Durkheim found an apparent correlation between a particular religion (Protestantism) and a high suicide rate. The fourth stage of positivist methodology involves a search for causal connections. If there is a strong correlation between two or more types of social phenomena, then a positivist sociologist might suspect that one of these phenomena was causing the other to take place. However this is not necessarily the case and it is important to analyse the data carefully before any such conclusion can be reached. The example of class and criminality can be used to illustrate this point. Many sociologists have noted a correlation between being working class and a relatively high chance of being convicted of a crime. Positivists believe that multivariate analysis can establish causal connections between two or more variables. If these findings are checked in a variety of contexts, then the researchers can be confident that they have attained the ultimate goal of positivism: a law of human behaviour. Durkheim claimed to have discovered laws of human behaviour that governed the suicide rate. According to Durkheim, the suicide rate always rose during an economic boom or slump. Positivists and Durkheim, then, believe that laws of human behaviour can be discovered by the collection of objective facts about the social world in a statistical form, by the careful analysis of these facts, and by repeated checking of findings in a series of contexts. From this point of view humans have little or no choice about how they behave. Durkheim conceived of sociology as the scientific study of a reality sui generis, a clearly defined group of phenomena different from those studied by all other sciences, biology and psychology included. It was for these phenomena that Durkheim reserved the term social facts, i.e., "a category of facts which present very special characteristics: they consist of manners of acting, thinking, and feeling external to the individual, which are invested with a coercive power by virtue of which they exercise control over him." Since these facts consisted of actions, thoughts, and feelings, they could not be confused with biological phenomena; but neither were they the province of psychology, for they existed outside the individual conscience. It was to define the proper method for their study that Durkheim wrote ‘The Rules of Sociological Method’ in 1895. His work on suicide, of which the discussion and analysis of anomie forms a part, must be read in this light. Once he discovered that certain types of suicide could be accounted for by anomie, he could then use anomic suicide as an index for the otherwise immeasurable degree of social integration. Durkheim distinguished between types of suicide according to the relation of the actor to his society. When the restraints of structural integration, as exemplified in the operation of organic solidarity, fail to operate, men become prone to egoistic suicide; when the collective conscience weakens, men fall victim to anomic suicide. Advantages of official statistics: Availability – It may be that official statistics are the only available source in a particular sociological area of interest e.g. when studying suicide. Practicality – The researcher does not have to spend time and money collecting his/her own information. It may be unnecessary for a researcher to create some forms of data using primary methods when such data already exists. Examination of trends/changes over time – Using statistical data drawn from a number of different years it is possible to see how something has changed over a long period. Comparison – Statistics can be used for inter-group comparisons (e.g. the differences between middle and working class) as well as cross-cultural comparisons (e.g. a comparative study of crime rates in different countries). “Before” and “after” studies – For example, you can use official data to examine the effect that changes in the law regarding divorce have by seeing the number of divorces before and after. Disadvantages of official statistics: Statistics are not always reliable. People may to lie to make them look better. Therefore, can we trust the methods through which these statistics are obtained? Statistics give us generalisations; they do not reflect a reality, they impose one. It has been argued that official statistics simply show a person’s judgement rather than objective facts. The research may have been collected for a different purpose therefore the data will not necessarily reflect the truth. The basis for the collection of stats by the governments may change over time. Any statistical account will represent only a ‘snapshot’ of social interaction. Antipositivism (also known as interpretivism) is the view in social science that the social realm may not be subject to the same methods of investigation as the natural world; that academics must reject[need quotation to verify] empiricism and the scientific method in the conduct of social research. Antipositivists hold that researchers should focus on understanding the interpretations that social actions have for the people being studied.[1][need quotation to verify]
Antipositivism relates to various historical debates in the philosophy and sociology of science. In modern practice, however, interpretivism may be equated with qualitative research methods, whilepositivist research is more quantitative.[1] Positivists typically use research methods such as experiments and statistical surveys, while antipositivists use research methods which rely more on ethnographic fieldwork, conversation/discourse analysis or open-ended interviews. Positivist and antipositivist methods are sometimes combined.[2]

Compare between Positivism and Interpretivism.

Positivism
Interpretivism
Goal of the research
Filling knowledge gap or finding universal laws
Solving problem , how do situational and cultural variations shape the reality
Reality
Single reality in the mind of people
No single reality – reality is different from context to context
Ontology
“What is the reality”
Realist/Objectivsit
Constructionist
Epistemology
“How can we get the reality”
Empiricist
Interpretivist
Research Approach
Deductive (you test the theory or test the explanation)
Inductive (you develop your theory)
Research Methods
Questionnaires
Focus Group, Observation, and Interviews.
Research Design
Fixed Design
Flexible Design
Thesis, Paper structure, or Conference paper
Abstract, Introduction, Literature Review, Theoretical Framework, Literature Review, Research Methodology, Data Collection, Analysis, and Validation.
Abstract, Introduction, Aims & Objectives, Research Questions, Research Methodology, Literature Review, Data Collection, Analysis, and Validation
Voice
Impersonal voice.
Personal voice.
Validity
Validated using statistics
Validating using interviews
Generalization
You could generalize
You could not generalize the idea.
Comparability
You can compare results from different studies since there are standardized statistical tools
You cannot compare easily since the observers are different
Names
Quantitative, Objectivism
Qualitative, Subjectivism
Scope
Problem as a whole are better understood if they are reduced into the simplest possible elements
Problems as a whole are better understood if the totality of the situation is looked at.

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