In other words, you take a piece of published research and repeat it, typically in an identical way to see if the results that you obtain are the same as the original authors. In some cases, you don't even redo the previous study, but simply request the original data that was collected, and reanalyse it to check that the original authors were accurate in their analysis techniques.
However, duplication is a very narrow view of replication, and is partly what has led some journal editors to shy away from accepting replication studies into their journals. The reality is that most research, whether completed by academics or dissertation students at the undergraduate, master's or doctoral level involves either generalisation or extension.
Alternately, replication can involve extending existing research to take into account new research designs , methods and measurement procedures , and analysis techniques. As a result, we call these different types of replication study: Duplication , Route B: Generalisation and Route C: In reality, it doesn't matter what you call them.
We simply give them these names because a they reflect three different routes that you can follow when doing a replication-based dissertation i.
Extension , and b the things you need to think about when doing your dissertation differ somewhat depending on which of these routes you choose to follow. When taking on a Route 1: Replication-based dissertation , we guide you through these three possible routes: Duplication ; Route B: Generalisation ; and Route C: Each of these routes has different goals, requires different steps to be taken, and will be written up in its own way.
To learn whether a Route 1: Replication-based dissertation is right for you, and if so, which of these routes you want to follow, start with our introductory guide: Sometimes the goal of quantitative research is not to build on or test theory, but to uncover the antecedents i.
Whilst you may not have heard the term before, a stylized fact is simply a fact that is surprising , undocumented , forms a pattern rather than being one-off, and has an important outcome variable , amongst other characteristics. A classic stylized fact was the discovery of the many maladies i. Such a discovery, made during the s, was surprising when you consider that smoking was being promoted by some doctors as having positive health benefits, as well as the fact that smoking was viewed as being stylish at the time Hambrick, The challenge of discovering a potential stylized fact, as well as collecting suitable data to test that such a stylized fact exists, makes data-driven dissertations a worthy type of quantitative dissertation to pursue.
Sometimes, the focus of data-driven dissertations is entirely on discovering whether the stylized fact exists e. These data-driven dissertations tend to be empirically-focused , and are often in fields where there is little theory to help ground or justify the research, but also where uncovering the stylized fact and its antecedents makes a significant contribution all by itself. On other occasions, the focus starts with discovering the stylized fact, as well as uncovering its antecedents e.
However, the goal is to go one step further and theoretically justify your findings. This can often be achieved when the field you are interested in is more theoretically developed e. We call these different types of data-driven dissertation: Empirically-focused and Route B: Data-driven dissertations , which we will be launching shortly, we introduce you to these two routes i.
Theoretically-justified , before helping you choose between them. Once you have selected the route you plan to follow, we use extensive, step-by-step guides to help you carry out, and subsequently write up your chosen route. For example, a researcher might look at violence in the workplace, focusing on when, where, or how it occurs. For example, take Hurricane Katrina. A researcher using this method will be trained during coursework and residencies in how to conduct this type of research, which involves specialized interviews and surveys with the people involved in the phenomenon.
Also called generic qualitative, generic inquiry, or other variations. So the researcher may be using similar methods, but will not have as thorough of a foundation of research available.
The researcher could run into problems with fewer data to analyze. Quantitative Quantitative research involves the empirical investigation of observable and measurable variables.
In this approach, data are collected by the researcher. Participants are recruited for the study, informed consent is obtained, and quantitative data are obtained either electronically or in person by the researcher. This approach allows the researcher to decide exactly what variables he or she is interested in exploring and how they will be operationalized in the study. Variables are measured using instruments whose psychometric properties reliability and validity have been established by other authors.
Data are analyzed using statistical techniques to assess the nature of the relationships between and among variables. The use of numerical evaluation is a specific feature of quantitative research. The data gathered will be sorted out and classified using numerical criteria, in this dissertation methodology. Due to the fact that quantitative method has a better lay out, there are dissertations which use this method in addition to qualitative methods.
In such cases the research would be done using qualitative method and the sorting of the data and the presentation will be done using quantitative methods.
This will make the research process easier as the qualitative method will help in gathering the necessary information and reaching a conclusion and the quantitative method will lay it out neatly. Quantitative research cannot be done while you are seeking answer to a question. If you do not have a specific idea of what the answer is, you will need to find the answer first, before using quantitative research to prove how you got the answer.
Without a very specific aim you cannot work using quantitative methods. Also, in quantitative research you need to provide precise data in the form of numerical or graphical presentation. Vague information or data which does not complement the expected conclusion will have no use in a quantitative method.
Quantitative Dissertations. The Quantitative Dissertations part of Lærd Dissertation helps guide you through the process of doing a quantitative dissertation. When we use the word quantitative to describe quantitative dissertations, we do not simply mean that the dissertation will draw on quantitative research methods or statistical analysis techniques.
"A Quantitative Study of Teacher Perceptions of Professional Learning Communities' Context, Process, and Content" (). Seton Hall .
Whilst we describe the main characteristics of qualitative, quantitative and mixed methods dissertations, the Lærd Dissertation site currently focuses on helping guide you through quantitative dissertations, whether you are a student of the social sciences, psychology, education or business, or are studying medical or biological sciences, sports science, . Quantitative Dissertation Consulting Statistics is a mathematical science that is used for data analysis, interpretation, explanation, and presentation of the data. Doctoral candidates require quantitative dissertation consulting because professional statisticians provide the expertise needed to effectively conduct the research, analyze the data and .
All research reports (including dissertations) begin with an introduction describing the problem under investigation in quantitative studies and need for the study in qualitative studies and its background, its relevance to the field, and the assumptions and the limitations of the study. The dissertation methodology influences the outcome of your research to a big extent. Hence it is important to make the right choice of methodology while handling a dissertation project.