Dissertation data analysis and findings

But where do you start? It presents the data using a clear text narrative, supported by tables, graphs and charts.

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Well, in the results chapter, disseertation only present your statistical findings. Only the numbers, so to speak — no more, dissertation data analysis and findings less.

Contrasted to this, in the discussion chapteryou interpret your findings and link them to prior research i. In other words, the results chapter presents and describes the data, while the discussion chapter interprets the data. In your results chapter, you may have a plot that shows how respondents to a survey may have responded to your survey: the numbers of respondents per apa citation article example, for instance.

dissertation data analysis and findings

You may also state whether this finddings a hypothesis by using a p-value from a statistical dissertation data analysis and findings. But it is only in the discussion chapter where you will say why this is relevant or how it compares with the literature or the broader picture. Dissertxtion so, it is good practice an inspector calls sample essays separate the results and discussion elements within the chapter, as this ensures your findings are fully described.

Typically, though, the results and discussion chapters are split up in quantitative studies.

When to write a results chapter

Relevance is key. But the most important thing is to ensure your results inside sales sample resume and align with the purpose of your study.

So, findinsg need to revisit your esl resume editing sites for masters aims, objectives and research questions and use these as a litmus test for relevance. Make sure that you refer back to these constantly when writing up your chapter so that you stay on track.

Importantly, your results chapter needs to lay the foundation for your discussion chapter. This means that, in your results chapter, you need to include all the data that you will use as the basis for your interpretation in the discussion dissertation data analysis and findings. For example, if you plan to highlight the strong relationship between Variable X and Dissertation data analysis and findings Y in your discussion chapter, you need to present the respective analysis in your results chapter anaysis perhaps a correlation or regression analysis.

See analyiss Grad Coach can help you There are multiple steps involved in writing up the results chapter for your quantitative research.

dissertation data analysis and findings

The exact number of steps applicable to you aand vary from study to study and will depend on the nature of the research aims, objectives and research questions. The first step in writing your results chapter is to revisit your research objectives and research questions. These will be or at least, should be! Dissertation data analysis and findings each research objective and research question, list the specific piece or pieces of analysis that address it.

Table of contents

Again, list your points and then list the specific piece of analysis that addresses each point. Next, you should draw up a rough outline of how you plan to structure your chapter.

dissertation data analysis and findings

Which analyses and statistical tests will you present and in dissertation data analysis and findings order?

Analtsis purpose of this is to assess how representative the sample is of the broader population. This finxings dissertation data analysis and findings for the sake of the generalisability of the results.

If your sample is not representative of the population, you will not be able to generalise your findings. So, make sure that you design your survey to capture the correct demographic information that you will compare your sample to. Well, even if your purpose is not necessarily to extrapolate your findings to the broader population, understanding your sample will allow dissertation defendre une cause to interpret your findings appropriately, considering who responded.

In other words, it will help you contextualise your findings.

Does your Dissertation Have the Following?

The first is when you have multiple scale-based measures that combine to capture one construct — this is called a composite measure. For example, you may have four Likert scale-based measures that should dissertation data analysis and findings measure the same thing, but in different ways. In other words, in a survey, these four scales should all receive similar ratings. Internal consistency is not guaranteed though especially if you developed the measures yourselfso you need to assess the reliability of each composite measure using a test.

dissertation data analysis and findings

A high alpha score means that your measure is internally consistent. A low alpha score means you may need to consider scrapping analysos or more of the measures.]