Get Help to Analyze Quantitative Data for a  Dissertation

A dissertation/thesis is an academic document that follows the research process to address a specific research question or hypothesis. Quantitative research involves evaluating and analyzing phenomena in a numerical manner using empirical methods. Capstone-Dissertation Writing Services offers the best quantitative dissertation, thesis, and capstone writing services.

We specialize in providing outstanding services to masters and doctoral students who want to successfully complete their quantitative research. We have trained academic writers who are professional in offering help in the following areas:

• Topic/title formulation.
• Reviewing the literature.
• Developing quantitative research questions and hypotheses.
• Quantitative research design.
• Developing valid and reliable data collection tools. E.g. Closed-ended questionnaires and likert-scale questionnaires for quantitative data collection.
• Data analysis using SPSS, R, STATA, and SAS software.
• Data presentation using graphs, tables, and charts.
• Writing the discussion by comparing the results with the literature review.
• Writing the conclusion and recommendations chapter.
• Writing the reference list or bibliography using various styles such as APA, Harvard, Chicago, MLA, AMA, among others.
• Writing the appendices.
• Editing and proofreading.
• Revising the dissertation, thesis, or capstone project based on your supervisor’s feedback.

Understanding Quantitative Research

Scholars normally use quantitative design, qualitative design, or mixed methods design in for dissertations, theses, or capstone projects. Quantitative design has the advantage of enabling a scholar to study large groups of people using a sample and making generalizations. Quantitative research can be experimental or non-experimental.

Experimental research involves specific hypotheses are created from a theory that is then tested by experiment. Non-experimental research, on the other hand, uses existing situations in the field to study phenomena. It is used when there is a need for descriptive quantitative data or when conducting a true experiment is impractical. Non-experimental research includes forms such as causal-comparative research, correlational research, and descriptive research.

Quantitative research also plays a role in discovering theory. It could also be exploratory, thus being used to discover relationships, interpretations, and characteristics of subjects that suggest new theory and define new problems.

When used for exploratory purposes, research questions are used instead of specific hypotheses. Scholars who need help with quantitative research for their dissertations or theses and are not sure how to proceed, can get expert help by consulting with us. Our company continues to assist graduate and PhD students to make the best choice of design for their research.

Developing a Title, Research Questions, and Hypotheses for a Quantitative Dissertation

(a). Formulating a Topic/Title for a Dissertation

A research title is an important part of a quantitative dissertation. To develop a research title, you need to first identify a gap or a research problem within your area of interest. Pose a brief question that needs to be answered regarding the research problem. Then, research to familiarize yourself with what other researchers have done concerning that problem.

The various sources of ideas in developing a title for a quantitative dissertation would be brainstorming, reading existing literature such as books and journals, scanning previous research projects, among others. You will come up with several themes and topics that can be used for your dissertation.

To narrow down, consider the characteristics of a good quantitative dissertation title. The title should be brief, precise, and informative. Usually, it should be up to twelve words.

The title gives a guideline to the next step of the quantitative dissertation which involves developing hypotheses or generating quantitative research questions. You should also consider your personal goals as a researcher which involves, the time it takes to complete the quantitative dissertation, revise it, and disseminate the results.

(b). Developing Hypotheses or Research Question(s)

A research hypothesis is a statement that shows the relationship between variables. The research hypotheses of a quantitative dissertation should enable the scholar to test the stated variable relations. The hypothesis should be simple, specific, and clear; able to be empirically tested and verified. It is derived from the research problem, literature review, and conceptual framework.

You can formulate the hypotheses by researching on the problem you have identified. This would incorporate the source of the research problem and the objectives in search of the solution. Also, the hypotheses for quantitative dissertation could be formulated by assessing data and records from previous studies in the area of interest.

Research questions in a quantitative dissertation inquire about the relationships among the variables that you are seeking to address. They are mostly used in social research such as surveys. Research questions are formulated from existing literature. If you are intending to buy a quantitative dissertation, thesis, or capstone project, we will be glad to develop your hypotheses and research questions, or guide you on how to go about it.

Sampling Technique and Data Collection

Selecting a sample from the existing population to be studied is important in quantitative dissertation. The steps of selecting a sample start with identifying the population you intend to study. You then choose a sampling technique, determine the sample size, and finally select the sample. Sampling techniques can be random or non-random.

The research instrument used to collect the data should also be stated and justified. When using an existing instrument, the established validity and reliability scores of the instrument should be provided. For online surveys such as Suyvey Monkey, identify steps used in administering the survey and following up to ensure a high response rate.

When selecting a data collection tool, consider the nature, scope, and object of inquiry, availability of funds, the time available, and the Precision required in your research. If you are facing challenges in getting a valid and reliable instrument, you can hire a quantitative research expert to develop an instrument for you from our team of professionals.

Quantitative Data Preparation and Analysis

Collected data is processed before the final analysis. Activities involved in preparation include editing of data, coding data, classification of the data, and tabulation. The scholar should examine the collected raw data to detect and correct errors and omissions. After editing the collected data, you may assign symbols to the data which are then categorized or classified. This process is called coding and classification of data. Finally, arrange the data in a logical order in a process called tabulation.

Once you have processed the raw data, analyze it to obtain results that are used to draw inferences for the research hypotheses or questions. In the process of analysis, you need to report information about the number of participants who did not return the survey. This can be achieved using a table of numbers and percentages to describe the respondents and non-respondents. You then determine the method you will use to determine the response bias.

The next step is providing the plan used for descriptive analysis of the data. This indicates the means, standard deviations, and range of scores of the variables used in the study. Then, identify the statistics and the statistical computer program used for testing the hypotheses and the major inferential analysis conducted in the research study. Finally, present the analyzed data in tables or figures and interpret the results for the hypotheses and the research questions.

The interpretation of results shows whether the hypotheses or questions were supported or were refuted. Indicate the significance of the results, drawing on past literature review, the theory used in the study, or persuasive logic that might explain the results. Any effects on results due to inadequate experimental procedures, such as threats to internal validity, should be addressed.

The generalization of the results to certain people, settings, and times is also stated. Finally, the implications of the results for the population studied are indicated for future research. This article is just a generic guide for quantitative data analysis process used by scholars, for more detailed and personalized assistance, contact us by live chat and we will work together to ensure the success of your dissertation, thesis, or capstone project. Our quantitative data analysts are the best - they are experienced statisticians and can make use of SPSS, STATA, R, and SAS programs.