Quantitative Research

Chapter 1: Introduction


Introduction


In this section, begin by providing a brief overview of your research topic. Clearly articulate the context and relevance of your study, and establish the background that led to the formulation of your research questions. Engage your readers by identifying the gaps or challenges in existing literature that your research aims to address.


Conceptual Framework


Develop a conceptual framework that serves as the theoretical foundation for your study. This should include a comprehensive review of relevant theories and models that underpin your research. Clearly outline how these concepts interrelate and contribute to understanding your research problem.


Statement of the Problem


Define the specific problem or issue your research seeks to investigate. Clearly articulate the gaps in knowledge or areas that require further exploration. Use concise and precise language to communicate the research questions or hypotheses guiding your study.


Significance of the Study


Explain the importance and potential impact of your research. Highlight how your study contributes to existing knowledge, addresses practical implications, or offers insights that could benefit academia, practitioners, or society at large.


Scope and Limitations


Define the boundaries of your research by specifying what is included (scope) and excluded (limitations). Clearly state the parameters within which your study operates and acknowledge any potential constraints that may affect the generalizability of your findings.


Definition of Terms


Provide clear and concise definitions for key terms and concepts used in your study. This ensures a common understanding among readers and avoids ambiguity in interpretation. Include both operational and conceptual definitions where applicable.


Chapter 2: Review of Related Literature


Citations


- Carefully identify and gather relevant literature sources, including peer-reviewed articles, books, and other scholarly works related to your research topic.
- Use standardized citation styles such as APA, MLA, or Chicago to format your citations consistently.
- Ensure accuracy by cross-referencing the citation details with the original sources.


Synthesis


- Analyze and synthesize the information from your selected sources, identifying patterns, trends, and gaps in the existing literature.
- Organize the literature in a coherent manner, highlighting key findings and theories relevant to your research.


Chapter 3: Methodology


Research Design


Clearly specify the type of research design employed (e.g., Descriptive, Experimental, Correlational, Case study, Quasi-Experimental) and justify its appropriateness for your study. Next, Outline the overall structure and approach that will guide your investigation.


Participants of the Study


Clearly define the characteristics of the participants in your study, including demographics and any relevant inclusion or exclusion criteria.


Research Instrument


Describe the tools and instruments used to collect data, such as surveys, questionnaires, or interviews. Provide rationale for their selection.


Research Procedure


Detail the step-by-step process of conducting your research, ensuring clarity and replicability. Include information on recruitment, data collection, and ethical considerations.


Statistical Treatment of Data


Clearly outline the statistical methods and techniques that will be employed to analyze the collected data. Justify your choices based on the nature of your research questions and data.


Chapter 4: Data Analysis


Identify your research questions


Research questions in both quantitative and qualitative research are questions that simplify the purpose statement down to particular questions that researchers seek to answer. In contrast to the simple and concise statement found in a purpose statement, researchers usually indicate several research questions in order to thoroughly investigate an issue. Research questions appear in both quantitative and qualitative studies, but their components may vary based on the type of study.


Define variables you will be collecting and measuring


Before you jump into the actual data collection, take a moment to figure out exactly what you're looking for. Define the specific things you want to measure and collect. This upfront work is like setting the stage for your research. It ensures that you have a clear plan and know exactly what aspects you're investigating. Getting these details straight beforehand makes the data collection process smoother and ensures that you're focused on the right things. It sets you up for a more straightforward and reliable analysis later on, helping you get the most out of your research. This also allows you to formulate and validate research questions you will ask from your participants.


Consider the procedures that will be used to filter out unnecessary data


Once you've collected data from your participants, it's important to give it a good read-through before diving into the analysis. This step helps filter out any information that might not be relevant. Essentially, you're making sure you're focusing on the important details and not getting sidetracked. This quick review is like a clean-up, ensuring that the analysis is based on the meaningful stuff and making the results more dependable.


Specify the quantitative software data analysis tools that will be used


Specify the tools you'll use for analyzing the data collected from your participants. This step is crucial because it outlines the methods and instruments that will translate raw data into meaningful insights. For instance, if you're dealing with survey responses, spreadsheet software like Microsoft Excel can be handy for basic analyses and visualization. These tools help uncover patterns, relationships, or trends within the data, allowing you to draw informed conclusions. By stating the tools you'll use to analyze data, you're essentially showing how you'll turn raw information into useful insights. This clarity not only makes your research process transparent but also helps others understand and replicate your analysis, making your findings more credible.


To describe, analyze, and summarize data, conduct a variety of analyses


Examples of data analyses include the mean, which represents the average of values in a dataset, and the standard deviation, indicating the variation of other variables from the mean and emphasizing the potential impact of an intervention. These analyses are important because they help researchers understand the typical value in a dataset (mean) and how much individual data points vary from this average (standard deviation). For example, the mean gives you a central reference point, showing the typical value, while the standard deviation indicates how spread out the data is. In experiments or interventions, changes in the mean or an increase in standard deviation can signal an impact, providing valuable insights into the effectiveness of the intervention. So, these tools are crucial for uncovering patterns and making sense of research results.


Discuss the various types of table that will be used to convey statistical reports


Explore the different types of tables that will be employed to present statistical reports. This is significant because the choice of tables plays a key role in conveying complex information in a clear and organized manner. Tables are visual aids that enhance the understanding of statistical data by providing a structured format for presenting numerical information. For instance, frequency tables can show the distribution of data, while comparative tables can highlight differences between groups or variables. By discussing the types of tables to be used, you're ensuring that your audience can easily comprehend and interpret the statistical findings, contributing to the effectiveness and accessibility of your research communication.


Steps in Compiling Data


Note: The aforementioned steps in compiling statistical data is only suitable in using the latest version of Excel or/and WPS.


COUNTIF Function:

  • Click on the "Formulas" tab, then go to "Statistical" and pick "COUNTIF."

    • EXAMPLE: If you want to count how many times the word "apple" appears in cells A1 to A10, you'd write =COUNTIF(A1:A10, "apple").



    3D Pie Chart Creation:

  • Click on the "Insert" tab, choose "Pie Chart," and go for "3D Pie."
  • Delete the chart title, and if you want to show numbers, click on the chart, choose "Data Labels," and then "More Options."

    • EXAMPLE: Represent your survey responses in cells B1 to B5 with a 3D Pie Chart.



    Mean and Standard Deviation Analysis:

  • Copy your numbers to a new sheet called "Sheet 2."
  • Find the average by clicking on "Formulas," then "AutoSum," and pick "Average."
  • Format the number to look nice by going to the "Home" tab.

    • EXAMPLE: If your numbers are in cells B1 to B10 on "Sheet 2," the average formula is =AVERAGE(Sheet2!B1:B10).



    Standard Deviation Formula:

  • To find how spread out your numbers are, use =STDEV.P( and drag it down after finding the average.

    • EXAMPLE: If your numbers are in cells B1 to B10 on "Sheet 2," the formula is =STDEV.P(Sheet2!B1:B10).



    Composite Mean and Standard Deviation:

  • Combine your average and spread out numbers to get a better picture.


    • Table Creation:

  • Make a table and make it look neat by removing the lines around it.

    • EXAMPLE: Design a table in cells D1:E5 with no lines and use Arial 9 font.



    Interpretation and Citations:

  • Explain what your numbers mean. If you use information from other research (like your Review of Related Literature), mention it.

    • EXAMPLE: If your data shows people prefer apples, explain why based on what you read in your Review of Related Literature.



    Chapter 5: Summary of findings, Conclusion, Recommendations


    Note: Start with an Introductory Statement consisting of only 2 sentences that includes the objective, purpose of the chapters and parts.


    Summary of findings


    The Summary section serves as a concise overview of the research, encompassing approximately two pages. It revisits the research's rationale, posing questions, defining scope, and outlining objectives. Following this, it articulates the research framework, model, or hypothesis, detailing the research design and methods of data collection.

    Moving on to the main findings, the Summary provides a brief presentation of outcomes derived from data analysis. Without delving into statistical intricacies such as t-tests, the section maintains brevity. It is crucial to revisit the initially set objectives and assess whether they were accomplished. If objectives remain unmet, providing compelling reasons is essential.

    The Summary intentionally refrains from introducing new elements, whether variables, interpretations, or data. The focus remains on summarizing the descriptive analysis of all data, highlighting key discoveries from Chapter 4, and presenting an overarching summary of major results.


  • Descriptive analysis of all data
  • Important findings based on the chapter 4
  • Summary of major results

    • Note: keep it simple and don't include any statistical terms Recommended : 1-2 paragraphs (1 and 1/2 pages) 10 sentences


    Conclusion


    Conclusions aren’t simply an overview of a paper. Instead, they should reiterate why your research is important. While it is helpful to include a brief summary, that is only the beginning. If done well, conclusions can leave readers feeling both satisfied yet hungry for more. Effective conclusions help readers reflect on what they just read, draw connections to existing knowledge, and spark their desire to further explore the subject. Ultimately, your conclusion should help readers answer the following question: Why should I care about this topic?


  • keep it short. While there is no hard and fast rule on length, conclusions are typically one paragraph long; however, you may find some that are two or three paragraphs long.
  • Start with the statement "Based from the findings of the study, the following conclusions were drawn:"
  • It should be on bulleted form

    • Note: Number of paragraphs are based on L2 or “Is there” questions in the SOP


    Recommendations


    The final section of the concluding chapter may contain suggestions on how to extend the work in future.

    A good source of such suggestions is the limitations of your study. Here, you can suggest one or two ways to overcome these limitations. When reviewing the literature, you may also come across a related research gap that is not considered in your study. Similarly, in analyzing the data, it may strike you that there is a different way to analyze the data. Being creative is part of research (Ulibarri et al., 2019).


  • Start with the statement "Based from the conclusions of the study, the following are recommended:"

  • It should be on number form
  • It should be Logical, specific, attainable and relevant

    • Note: Minimum of 4 recommendations