METODE PENELITIAN KUANTITATIF DALAM KAJIAN LINGKUNGAN Bahan kajian Metode Penelitian Kajian Lingkungan Diabstraksikan o

METODE PENELITIAN KUANTITATIF DALAM KAJIAN LINGKUNGAN Bahan kajian Metode Penelitian Kajian Lingkungan Diabstraksikan oleh Soemarno, PMPSLP PPSUB 2011

Quantitative research In the social sciences, quantitative research refers to the systematic empirical investigation of quantitative properties and phenomena and their relationships. 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

ImageCharacteristics of the qualitative-quantitative research continuum

In across-stage mixed model research, quantitative and qualitative approaches are mixed across at least two of the stages of research.

Principles OF POSITIVISM In its strongest original formulation, positivism could be thought of as a set of five principles: The unity of the scientific method – i.e., the logic of inquiry is the same across all sciences (social and natural). The goal of inquiry is to explain and predict. Most positivists would also say that the ultimate goal is to develop the law of general understanding, by discovering necessary and sufficient conditions for any phenomenon (creating a perfect model of it). If the law is known, we can manipulate the conditions to produce the predicted result.

Principles OF POSITIVISM Scientific knowledge is testable. Research can be proved only by empirical means, not argumentations. Research should be mostly deductive, i.e. deductive logic is used to develop statements that can be tested (theory leads to hypothesis which in turn leads to discovery and/or study of evidence). Research should be observable with the human senses (arguments are not enough, sheer belief is out of the question). Positivists should prove their research using the logic of confirmation.

Principles OF POSITIVISM Science does not equal common sense. Researchers must be careful not to let common sense bias their research. The relation of theory to practice – science should be as value-free as possible, and the ultimate goal of science is to produce knowledge, regardless of any politics, morals, or values held by those involved in the research. Science should be judged by logic, and ideally produce universal conditionals: For all conditions of X, if X has property P and P=Q, then X has property Q. Statements must be true for all times and places.

Positivism in science today: Constructive empiricism • The key features of positivism as of the 1950s, as defined in the "received view“ , are: • A focus on science as a product, a linguistic or numerical set of statements; • A concern with axiomatization, that is, with demonstrating the logical structure and coherence of these statements; • An insistence on at least some of these statements being testable, that is amenable to being verified, confirmed, or falsified by the empirical observation of reality; statements that would, by their nature, be regarded as untestable included the teleological; thus positivism rejects much of classical metaphysics. • The belief that science is markedly cumulative;

Positivism in science today: Constructive empiricism • The key features of positivism as of the 1950s, as defined in the "received view“ , are: • The belief that science is predominantly transcultural; • The belief that science rests on specific results that are dissociated from the personality and social position of the investigator; • The belief that science contains theories or research traditions that are largely commensurable; • The belief that science sometimes incorporates new ideas that are discontinuous from old ones; • The belief that science involves the idea of the unity of science, that there is, underlying the various scientific disciplines, basically one science about one real world.

QUANTITATIVE RESEARCH Quantitative research is used widely in social sciences such as psychology, sociology, anthropology, and political science. 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 qualitative research methods.

Quantitative research is used to measure how many people feel, think or act in a particular way. These surveys tend to include large samples - anything from 50 to any number of interviews. Structured questionnaires are usually used incorporating mainly closed questions - questions with set responses. There are various vehicles used for collecting quantitative information but the most common are on-street or telephone interviews.

Qualitative versus Quantitative Research:Key Points in a Classic Debate Features of Qualitative & Quantitative Research

Main Points • Qualitative research involves analysis of data such as words (e.g., from interviews), pictures (e.g., video), or objects (e.g., an artifact). • Quantitative research involves analysis of numerical data. • The strengths and weaknesses of qualitative and quantitative research are a perennial, hot debate, especially in the social sciences. The issues invoke classic 'paradigm war'. • The personality / thinking style of the researcher and/or the culture of the organization is under-recognized as a key factor in preferred choice of methods. • Overly focusing on the debate of "qualitative versus quantitative" frames the methods in opposition. It is important to focus also on how the techniques can be integrated, such as in mixed methods research. More good can come of social science researchers developing skills in both realms than debating which method is superior.

Recommended Links • Qualitative versus Quantitative - http://www.gifted.uconn.edu/siegle/research/Qualitative/qualquan.htm - a table (similar to above), summarizing characteristics of qualitative and quantitative research in more detail • 2. Qualitative versus Quantitative Design - http://www.kelcom.igs.net/~nhodgins/quant_qual.html - another table (like above) • 3. The Qualitative versus Quantitative Debate - http://writing.colostate.edu/references/research/gentrans/pop2f.cfm - good overview, but the layout is flat and difficult to skim-read • 4. Qualitative vs Quantitative analysis - http://www.ling.lancs.ac.uk/monkey/ihe/linguistics/corpus3/3qual.htm - reasonable overview, with linguistics focus

QUALITATIVE RES. Qualitative research explores attitudes, behaviour and experiences through such methods as interviews or focus groups. It attempts to get an in-depth opinion from participants. As it is attitudes, behaviour and experiences which are important, fewer people take part in the research, but the contact with these people tends to last a lot longer. Under the umbrella of qualitative research there are many different methodologies.

Quantitative research Quantitative research generates statistics through the use of large-scale survey research, using methods such as questionnaires or structured interviews. If a market researcher has stopped you on the streets, or you have filled in a questionnaire which has arrived through the post, this falls under the umbrella of quantitative research. This type of research reaches many more people, but the contact with those people is much quicker than it is in qualitative research.

Qualitative versus quantitative inquiry Over the years there has been a large amount of complex discussion and argument surrounding the topic of research methodology and the theory of how inquiry should proceed. Much of this debate has centred on the issue of qualitative versus quantitative inquiry – which might be the best and which is more ‘scientific’. Different methodologies become popular at different social, political, historical and cultural times in our development, and, in my opinion, all methodologies have their specific strengths and weaknesses. These should be acknowledged and addressed by the researcher. Certainly, if you were to do so, it would help you to think about your research methodology in considerable depth.

Deciding which methodology is right for you Don’t fall into the trap which many beginning (and experienced) researchers do in thinking that quantitative research is ‘better ’ than qualitative research. Neither is better than the other – they are just different and both have their strengths and weaknesses.

Deciding which methodology is right for you What you will find, however, is that your instincts probably lean you towards one rather than the other. Listen to these instincts as you will find it more productive to conduct the type of research with which you will feel comfortable, especially if you’re to keep your motivation levels high. Also, be aware of the fact that your tutor or boss might prefer one type of research over the other. If this is the case, you might have a harder time justifying your chosen methodology, if it goes against their preferences.

Qualitative and quantitative research are the two main schools of research, and although they are often used in tandem, the benefits and disadvantages of each are hotly debated. Particularly in the social sciences, the merits of both qualitative and quantitative research are fought over, with intense views held on both sides of the argument. It is generally agreed upon, however, that there are some phases of research where one or the other is clearly more useful than the other, and so few people completely dismiss either.

Quantitative research is probably the least contentious of the two schools, as it is more closely aligned with what is viewed as the classical scientific paradigm. Quantitative research involves gathering data that is absolute, such as numerical data, so that it can be examined in as unbiased a manner as possible. There are many principles that go along with quantitative research, which help promote its supposed neutrality. Quantitative research generally comes later in a research project, once the scope of the project is well understood.

The main idea behind quantitative research is to be able to separate things easily so that they can be counted and modeled statistically, to remove factors that may distract from the intent of the research. A researcher generally has a very clear idea what is being measured before they start measuring it, and their study is set up with controls and a very clear blueprint. Tools used are intended to minimize any bias, so ideally are machines that collect information, and less ideally would be carefully randomized surveys. The result of quantitative research is a collection of numbers, which can be subjected to statistical analysis to come to results.

Qualitative research, on the other hand, is a much more subjective form of research, in which the research allows themselves to introduce their own bias to help form a more complete picture. Qualitative research may be necessary in situations where it is unclear what exactly is being looked for in a study, so that the researcher needs to be able to determine what data is important and what isn’t. While quantitative research generally knows exactly what it’s looking for before the research begins, in qualitative research the focus of the study may become more apparent as time progresses.

Qualitative and Quantitative Research: Conjunctions and Divergences Vol 2, No 1 (2001) Edited by Margrit Schreier & Nigel Fielding Introduction: On the Compatibility between Qualitative and Quantitative Research Methods Nigel Fielding, Margrit Schreier The Logic of Relating Qualitative and Quantitative Method Sociological Explanations between Micro and Macro and the Integration of Qualitative and Quantitative Methods Udo Kelle

Combination and Integration of Qualitative and Quantitative Analysis Philipp Mayring Constructivist Realism: An Ontology That Encompasses Positivist and Constructivist Approaches to the Social Sciences Gerald Cupchik Gerald Cupchik Strategies in Qualitative and Quantitative Research Harald Witt

Different Approaches for Inter-Relating Qualitative and Quantitative Method Seeing Our Quantitative Counterparts: Construction of Qualitative Research in a Roundtable Discussion Jean A. Saludadez, Primo G. Garcia The Quantitative/Qualitative Debate and Feminist Research: A Subjective View of Objectivity Nicole Westmarland The Logographic Analysis of Social Processual Texts Annette Schmitt, Ulrich Mees, Uwe Laucken Numerically Aided Phenomenology: Procedures for Investigating Categories of Experience Don Kuiken, David S. Miall

Innovative Applications of Methodological Inter-Relation How Do You Find Out What Really Matters for Public Acceptance—The Case of Swine Production Sites in Rural Communities Stefan Mann Understanding Online Communities Through Multiple Methodologies Combined Under a Postmodern Research Endeavour Natilene Irain Bowker On the Triangulation of Quantitative and Qualitative Data in Typological Social Research: Reflections on a Typology of Conceptualizing "Uncertainty" in the Context of Employment Biographies Alexander Jakob

quantitative research Use of sampling techniques (such as consumer surveys) whose findings may be expressed numerically, and are amenable to mathematical (statistical) manipulation enabling the researcher to estimate (forecast) future events or quantities. Read more: http://www.businessdictionary.com/definition/quantitative-research.html#ixzz14N3yE08e

Quantitative research is mainly concerned with numbers and data easily quantified. The most popular quantitative technique is the survey, often based on a large number of cases, where a broad overview of a market is required. Surveys can be administered by mail, telephone, face to face, or more recently by the Internet or World Wide Web. They usually take less time to complete by the respondant and most often require choosing between several responses rather than long verbal responses. In market research, surveys often aim to understand a target market better by breaking down the sample by demographics, lifestyle and usage behaviour.

QUANTITATIVE RESEARCH • 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 • Evaluation of results

Use of statistics 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.

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. 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.

Measurement Views regarding the role of measurement in quantitative research are somewhat divergent. Measurement is often regarded as being only a means by which observations are expressed numerically in order to investigate causal relations or associations. However, it has been argued that measurement often plays a more important role in quantitative research. For example, Kuhn argued that within quantitative research, the results that are shown can prove to be strange. This is because accepting a theory based on results of quantitative data could prove to be a natural phenomenon.

Quantitative methods Quantitative methods are research techniques that are used to gather quantitative data - information dealing with numbers and anything that is measurable. Statistics, tables and graphs, are often used to present the results of these methods. They are therefore to be distinguished from qualitative methods.

Quantitative methods 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 has become 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.

Quantitative methods Advocates of quantitative methods argue that only by using such methods can the social sciences become truly scientific; advocates of qualitative methods argue that quantitative methods tend to obscure the reality of the social phenomena under study because they underestimate or neglect the non-measurable factors, which may be the most important. The modern tendency (and in reality the majority tendency throughout the history of social science) is to use eclectic approaches.

Quantitative methods Quantitative methods might be used with a global qualitative frame. Qualitative methods might be used to understand the meaning of the numbers 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.

Quantitative Research Design In quantitative research your aim is to determine the relationship between one thing (an independent variable) and another (a dependent or outcome variable) in a population. Quantitative research designs are either descriptive (subjects usually measured once) or experimental (subjects measured before and after a treatment). A descriptive study establishes only associations between variables. An experiment establishes causality.

Quantitative Research Design For an accurate estimate of the relationship between variables, a descriptive study usually needs a sample of hundreds or even thousands of subjects; an experiment, especially a crossover, may need only tens of subjects. The estimate of the relationship is less likely to be biased if you have a high participation rate in a sample selected randomly from a population. In experiments, bias is also less likely if subjects are randomly assigned to treatments, and if subjects and researchers are blind to the identity of the treatments.

Quantitative Research Design In all studies, subject characteristics can affect the relationship you are investigating. Limit their effect either by using a less heterogeneous sample of subjects or preferably by measuring the characteristics and including them in the analysis. In an experiment, try to measure variables that might explain the mechanism of the treatment. In an unblinded experiment, such variables can help define the magnitude of any placebo effect.

Quantitative research is all about quantifying relationships between variables. Variables are things like weight, performance, time, and treatment. Researcher measure variables on a sample of subjects, which can be tissues, cells, animals, or humans. Researcher express the relationship between variable using effect statistics, such as correlations, relative frequencies, or differences between means.

TYPES OF STUDY Studies aimed at quantifying relationships are of two types: descriptive and experimental. In a descriptive study, no attempt is made to change behavior or conditions – researcher measure things as they are. In an experimental study, researcher take measurements, try some sort of intervention, then take measurements again to see what happened.

Descriptive Studies Descriptive studies are also called observational, because you observe the subjects without otherwise intervening. The simplest descriptive study is a case, which reports data on only one subject; examples are a study of an outstanding athlete or of a dysfunctional institution. Descriptive studies of a few cases are called case series. In cross-sectional studies variables of interest in a sample of subjects are assayed once and the relationships between them are determined. In prospective or cohort studies, some variables are assayed at the start of a study (e.g., dietary habits), then after a period of time the outcomes are determined (e.g., incidence of heart disease). Another label for this kind of study is longitudinal, although this term also applies to experiments.

Descriptive Studies Case-control studies compare cases (subjects with a particular attribute, such as an injury or ability) with controls (subjects without the attribute); comparison is made of the exposure to something suspected of causing the cases, for example volume of high intensity training, or number of alcoholic drinks consumed per day. Case-control studies are also called retrospective, because they focus on conditions in the past that might have caused subjects to become cases rather than controls.

Descriptive Studies A common case-control design in the exercise science literature is a comparison of the behavioral, psychological or anthropometric characteristics of elite and sub-elite athletes: you are interested in what the elite athletes have been exposed to that makes them better than the sub-elites. Another type of study compares athletes with sedentary people on some outcome such as an injury, disease, or disease risk factor. Here you know the difference in exposure (training vs no training), so these studies are really cohort or prospective, even though the exposure data are gathered retrospectively at only one time point. The technical name for these studies is historical cohort.

Experimental Studies Experimental studies are also known as longitudinal or repeated-measures studies, for obvious reasons. They are also referred to as interventions, because you do more than just observe the subjects. In the simplest experiment, a time series, one or more measurements are taken on all subjects before and after a treatment. A special case of the time series is the so-called single-subject design, in which measurements are taken repeatedly (e.g., 10 times) before and after an intervention on one or a few subjects.

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