Note 3. Qualitative Research Vs Quantitative Research


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Note 3. Qualitative Research Vs Quantitative Research

  2. 2. ASSIGNMENT 1 Describe with examples the differences between qualitative research and quantitative research. In what situation that a research needs to be conducted by means of mixtures of qualitative and quantitative methods. Qualitative research is a method of inquiry appropriated in many different academic disciplines, traditionally in the social sciences, but also in market research and further contexts. 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 just what, where,when. Hence, smaller but focused samples are more often needed, rather than large samples. Qualitative methods produce information only on the particular cases studied, and any more general conclusions are only hypotheses (informative guesses). Qualitative means a non- numerical data collection or explanation based on the attributes of the graph or source of data. For example, if you are asked to explain in qualitative terms a thermal image displayed in multiple colours, then you would explain the colour differences rather than the heat's numerical value.) First, cases can be selected purposefully, according to whether or not they typify certain characteristics or contextual locations. Secondly, the role or position of the researcher is given greater critical attention. This is because in qualitative research the possibility of the researcher taking a 'neutral' or transcendental position is seen as more problematic in practical and/or philosophical terms. Hence qualitative researchers are often exhorted to reflect on their role in the research process and make this clear in the analysis. Thirdly, while qualitative data analysis can take a wide variety of forms it tends to differ from quantitative research in the focus on language, signs and meaning as well as approaches to analysis that are holistic and contextual, rather than reductionist and isolationist. Nevertheless, systematic and transparent approaches to analysis are almost always regarded as essential for rigor. For example, many qualitative methods require researchers to carefully code data and discern and document themes in a consistent and reliable way.
  3. 3. Perhaps the most traditional division in the way qualitative and quantitative research have been used in the social sciences is for qualitative methods to be used for exploratory (i.e., hypothesis-generating) purposes or explaining puzzling quantitative results, while quantitative methods are used to test hypotheses. This is because establishing content validity - do measures measure what a researcher thinks they measure? - is seen as one of the strengths of qualitative research. While quantitative methods are seen as providing more representative, reliable and precise measures through focused hypotheses, measurement tools and applied mathematics. By contrast, qualitative data is usually difficult to graph or display in mathematical terms. Qualitative research is often used for policy and program evaluation research since it can answer certain important questions more efficiently and effectively than quantitative approaches. This is particularly the case for understanding how and why certain outcomes were achieved (not just what was achieved) but also answering important questions about relevance, unintended effects and impact of programs such as: Were expectations reasonable? Did processes operate as expected? Were key players able to carry out their duties? Were there any unintended effects of the program? Qualitative approaches have the advantage of allowing for more diversity in responses as well as the capacity to adapt to new developments or issues during the research process itself. While qualitative research can be expensive and time-consuming to conduct, many fields of research employ qualitative techniques that have been specifically developed to provide more succinct, cost-efficient and timely results. Rapid Rural Appraisal is one formalised example of these adaptations but there are many others. 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.
  4. 4. Quantitative research is used widely in social sciences such as 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. 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. 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. 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. 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 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.
  5. 5. Examples of quantitative research are:-  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. Multimethodology,or mixed methods research, is an approach to professional research that combines the collection and analysis of quantitative and qualitative data. The approach to mixed methods research occurs when the researcher cannot rely on either a quantitative or a qualitative method alone and must buttress his or her findings with a method drawn from the other research strategy. Its most typical form is when ethnographers employ structured interviewing or possibly a self-completion questionnaire, because not everything they need to know about is accessible through participant observation. This kind of need can arise for several reasons, such as the need for information that is not accessible to observation or to qualitative interviewing for example, systematic information about social backgrounds of people in a particular setting, or the difficulty of gaining access to certain groups of people. For example, Hochschild (1989) used qualitative analysis of time use in her study of working couples with children to assess levels of participation in everyday domestic work. This formed the basis for her qualitative exploration based on interviews and observation of the gender strategies that working couples use. The synopsis of differentiation is below 1 : 1 Alan Bryman, Emma Bell (2007). Business Research Methods. Second Edition. Oxford University Press.
  6. 6. QUANTITATIVE QUALITATIVE • It can be construed as a research strategy that • It can be construed as a research emphasizes quantification in the collection and strategy that usually emphasizes words analysis of data. rather than quantification in the collection and analysis of data. • It entails a deductive approach to the • Predominantly emphasizes an relationship between theory and research, in inductive approach to the relationship which the accent is placed on the testing of between theory and research, in which theories. the emphasis is placed on the generation of theories. • It has rejected the practices and norms • It has incorporated the practices and norms of of the natural scientific model and of the natural scientific model and positivism in positivism in particular in preference particular. for an emphasis on the way in which individual interpret their social world. • It embodies a view of social reality as an • It embodies the view of social reality external, objective reality. as a constantly shifting emergent property of individuals’ creation. • In broad, it was described as entailing the • Qualitative research tends to be collection of numerical data and as exhibiting concerned with words rather than view of relationship between theory and numbers. research as deductive, a predilection for natural science approach and as having an objectivist conception of social reality. ASSIGNMENT 2
  7. 7. Consider a problem that may face by a human resource manager at Malaysian Airline System Berhad (MAS), who wishes to test the effectiveness of two methods for training new sale executives. The company selects 22 trainees who are randomly divided into two experimental groups. One receives type A and the other type B training. The trainees are then assigned and managed without regard to the training they have received. At the year’s end, the manager reviews the performance of employees in these groups and finds the following results: A Group B Group Average hourly sales RM1500 RM1300 Standard deviations 225 251 Following a suitable standard statistical testing procedure, analyze the data and make appropriate recommendations. Since the sample is less than 30, so we will use t-test to test the hypothesis above. With small sample sized, normally distributed populations, and assuming equal population variances, the t- test is appropriate : ( x1 −x2 ) −( µ −µ )0 t = 1 2 1 1  S p2  +   n1 n2  Where ( u1 - u2 ) is the difference between the two population means S P 2 is associated with the pooled variance estimate : S 2= ( n1 − 1) S12 + ( n2 − 1) S22 p n1 + n2 − 2
  8. 8. Following the standard testing procedure, we will determine whether one training method is superior to the other. Null hypothesis. Ho : There is no difference in sales results produced by the two training methods. HA : Training method A produces sales results superior to those of method B. Statistical test. The t-test is chosen because the data are at least interval and the samples are independent. Significant level. ∞ = .05 (one-tailed test) Calculated value. t= (1500 – 1300) – 0 _ _ (10)(225)2 + (10)(251)2 (1/11 + 1/11) 20 = 200 = 1.97, d.f. = 20 101.63 There are n – 1 degrees of freedom in each sample, so total d.f. = (11-1) + (11-1) = 20 Critical test value. Enter Appendix Table F-2 with d.f. = 20, one-tailed test, ∞ = .05. The critical value is 1.725. Interpret. Since the calculated value is larger than the critical value (1.97 > 1.725), reject the null hypothesis and conclude that training group A is superior. ASSIGNMENT 3
  9. 9. Two hundred Muslim government officers in the state of Selangor selected at random from various levels of management were interviewed regarding their condern for halal products. The information was organized into the following table. Level of Management No concern Some concern Great concern Top management 15 13 12 Middle management 20 19 21 Supervisor 35 28 37 Following a suitable standard statistical testing procedure, analyze the data and make appropriate recommendations. Nonparametric Tests The chi-square (x2) test is appropriate for situations in which a test for differences between sample is required. It is especially valuable for nominal data but can be used with ordinal measurements. When parametric data have been reduced to categories, they are frequently treated with x2 although this result in a loss of information. Preparing to solve this problem is the same as presented earlier although the formula differs slightly. x2 = €€ (Oij - Eij)2 Eij In which Oij = Observed number of cases categorized in the ijth cell Eij = Expected number of cases under Ho to be categorized in the ijth cell The expected values have been calculated and are shown. The testing procedure is : 1. Null hyphotesis Ho : There is no difference in various levels of management and concern for halal products H1 : There is difference in various levels of management and concern for halal products. 2. Statistical test x2 is appropriate but it may waste some of the data because the measurement appears to be ordinal.
  10. 10. 3. Significance level ∞ = .05 with d.f. = (3-1) (3-1) = 4 4. Calculated value The expected distribution is provided by the marginal totals of the table. If there is no relationship between level of management and concern for halal products, there will be the same proportion of level of management and concern for halal product. The numbers of expected observations in each cell are calculated by multiplying the two marginal totals common a particular cell and dividing this product by n. Level of Management No concern Some Great Row concern concern Total Top level management 15 13 12 40 14 12 14 Middle level management 20 19 21 60 21 18 21 Supervisor 35 28 37 100 35 30 35 Column Total 70 60 70 200 x2 = (15 – 14 )2 + (13 – 12)2 + (12 – 14)2 + (20 – 21)2 + (19 – 18)2 + (21-21)2 14 12 14 21 18 21 (35 – 35)2 + (28 – 30)2 + (37 – 35)2 35 30 35 = 0.7912 5. Critical test value Enter Appendix Table F-3 and find the critical value 9.49 with ∞ = .05 and d.f. = 4 6. Interpret Since the calculated value is less than the critical value, the null hypothesis is accepted.