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This post will discuss a quantitative dissertation, its types, structure, and complete examples. A quantitative dissertation involves collecting and analyzing numerical data to answer a research question.
As a student, it is important to understand the options available and determine the best fit for the research. We hope this blog helps you navigate the process of selecting a data analysis approach for your quantitative dissertation.
For maximum knowledge and complete understanding, check out our quantitative dissertation examples alongside the strategies described below;
What is a Quantitative Dissertation?
The quantitative dissertation is a type of research design that generates numeric data. The subject of analysis is usually a phenomenon that can be measured and assigned numerical values (i.e., how often do people attend religious services?).
Statistical methods are commonly employed to examine relationships or trends in the data. These may include inferential statistics, which allow the researcher to make conclusions about a population based on a sample, or descriptive statistics, which are used to summarize the data.
Types of Quantitative Analysis Dissertation
The quantitative dissertation usually takes one of two forms:
- An empirical study, in which the researcher collects data through surveys or experiments; or
- A secondary analysis, in which the researcher uses an existing dataset.
The most important thing to remember about the quantitative dissertation is that it is not a collection of freestanding studies that happen to use numbers. Instead, it should be a coherent piece of work in which each chapter leads logically to the next.
How to Structure Your Quantitative Dissertation
Chapter 1: Introduction
In Chapter 1, you will need to introduce your topic and explain why it is important. You will also need to state your research question(s) and objectives and describe your methodology. This chapter should end with a clear statement of what you hope to achieve in your study.
Chapter 2: Review of Literature
In Chapter 2, you will review the existing literature on your topic to situate your research within the larger field. This chapter should include a comprehensive review of scholarly articles, journals, books, and other sources relevant to your topic. Keep in mind that this is not simply a list of everything written on your topic; it should be a well-organized synthesis of the literature that highlights gaps and opportunities for further research.
Chapter 3: Methodology
In Chapter 3, you will describe your research design and methods in detail. It includes specifying your participants (or describing how you will select them), explaining how you will collect data from them (e.g., surveys, interviews, experiments), and outlining your data analysis plan. Remember to align your methodology with the research questions you formulated in Chapter 1!
Chapter 4: Findings/Results
Broadly speaking, Chapter 4 presents the findings of your study. However, because different dissertation designs call for different data types (quantitative vs qualitative), this chapter will take on different forms depending on your methodology.
If you conducted an experiment or survey, this would be where you present descriptive statistics such as means, frequencies, and correlations; if you utilized existing data (e.g., census records), this would be where you conduct inferential statistical analyses to answer your research questions; if you relied on qualitative data (e.g., interviews), this would be where you present themes or patterns that emerged from your analysis.
Regardless of its form, Chapter 4 should provide readers with a clear understanding of what happened in your study and why it happened.
Chapter 5: Discussion/Implications
Chapter 5 interprets the findings presented in Chapter 4 and links them back to the literature reviewed in Chapter 2. Here you will discuss what these findings mean concerning what was already known about your topic (as summarized in Chapter 2). This chapter should also address any limitations inherent in your study and explain their implications for future research on this topic.
Some Quantitative Dissertation Examples
Here are some examples of quantifiable research questions that could be answered using a quantitative dissertation:
- How does the level of anxiety experienced by first-year college students affect their academic performance?
- What is the relationship between parental income and child obesity rates in the United States?
- Does exposure to violent media significantly impact aggressive behaviour in children?
As you can see, these questions can be answered using numerical data. And that's all there is to it! A quantitative dissertation is a research project using numerical data to answer a particular research question. It's not as intimidating as it sounds.
Conclusion
We hope this article has helped to demystify the quantitative dissertation for you. Remember, a quantitative dissertation is a research project using numerical data to answer a particular research question.
Choosing the right data analysis approach for your dissertation is a critical decision that will greatly impact the quality of your results. When selecting, consider the nature of your research project, the type of data you'll be collecting, and the logistics of your data collection process.
With careful consideration of these factors, you can be confident in choosing an approach that will set you up for success.
You can contact Premier Dissertation professionals for assistance or order an exceptional quantitative dissertation.
Explore the following examples to become the best dissertation writer;
