{"id":1081,"date":"2019-03-27T15:06:22","date_gmt":"2019-03-27T15:06:22","guid":{"rendered":"https:\/\/helpwithdissertation.com\/blog\/?p=1081"},"modified":"2019-04-08T14:27:39","modified_gmt":"2019-04-08T14:27:39","slug":"how-to-write-qualitative-data-analysis","status":"publish","type":"post","link":"https:\/\/helpwithdissertation.com\/blog\/2019\/03\/how-to-write-qualitative-data-analysis\/","title":{"rendered":"How To Write Qualitative Data Analysis"},"content":{"rendered":"\n

How To Write Qualitative Data Analysis<\/h2>\n\n\n\n
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So you want to grasp how to write qualitative data analysis<\/strong>. You\u2019ll pretty soon since you\u2019re already on the right page. Here, you\u2019ll learn what qualitative data analysis is. Most importantly, you\u2019ll learn how to carry out a qualitative data analysis. Additionally, you\u2019ll understand how qualitative data analysis differs from quantitative data analysis. Ready? Let\u2019s roll.<\/p>\n\n\n\n

The other name for qualitative data is descriptive data<\/strong>. Qualitative data is essentially non-numerical data<\/strong> that concerns itself with capturing\nconcepts and opinions. When you interview someone, you\u2019re collecting\nqualitative data. Similarly, when you make audio or video recordings, you\u2019re gathering\nqualitative data. Also, notes made while observing a certain phenomenon count\nas qualitative data. Now that we know what qualitative data is, let\u2019s learn\nwhat qualitative data analysis is.<\/p>\n\n\n\n

What\u2019s Qualitative Data Analysis and Why Does it Matter? <\/h2>\n\n\n\n

Qualitative data analysis refers to the process of working through qualitative data to glean useful information. The information you obtain from this exercise helps you develop a plausible explanation for a particular phenomenon. The process is hugely important as it reveals themes and patterns in the data you’ve gathered. <\/p>\n\n\n\n

Additionally, data analysis<\/strong> enables you to link your data to the objectives and research questions of your study. Also, the process helps you organize your data and interpret it. Most importantly, successful qualitative data analysis leads you to informed conclusions. What\u2019s more, the conclusions you end up with are verifiable. <\/p>\n\n\n\n

How Does Qualitative Data Analysis Differ from Quantitative Data Analysis? <\/h2>\n\n\n\n

As a researcher, you MUST understand how qualitative data analysis differs from quantitative data analysis. Gaining a clear understanding of the difference between the two helps you choose the right research method for your study. In addition, grasping the difference prevents you from getting sidetracked while executing the research methodology you’ve chosen. <\/p>\n\n\n\n

Here\u2019s the main difference. Qualitative data analysis helps researchers get useful information from non-numerical or subjective data. By contrast, quantitative data analysis is about mining knowledge from your data using statistical or numerical techniques. <\/p>\n\n\n\n

Some disciplines, especially those in the humanities and\nsocial sciences, tend to favor qualitative data analysis. Quantitative data\nanalysis, on the other hand, tends to find greater relevance within the\nsciences including chemistry, physics, and biology. <\/p>\n\n\n\n

How Researchers Approach Qualitative Data Analysis<\/h2>\n\n\n\n

There are 2 main approaches when it comes to qualitative data analysis. These approaches include the Deductive Approach<\/strong> and the Inductive Approach<\/strong>. As a student and future academic researcher, it\u2019s critical that you understand each approach. <\/p>\n\n\n\n

What the Deductive Approach is and When to Use it<\/h3>\n\n\n\n

The deductive approach is about analyzing data on the basis of a structure that you as the researcher have predetermined. The approach relies heavily on the research questions that inform your study. Your research questions should direct and guide you as you group and analyze the data you’ve collected. <\/p>\n\n\n\n

When should I use the deductive approach to qualitative data\nanalysis? A good question right there. Employ this approach when you can fairly\npredict the responses you might get from your sample population. The beauty of\nthis approach is that it\u2019s easy to use. There\u2019s more. The deductive approach\nworks fast. <\/p>\n\n\n\n

What the Inductive Approach is and When to Use it<\/h3>\n\n\n\n

Here\u2019s the main difference between the deductive approach\nand the inductive approach. The inductive approach, unlike the deductive\napproach, doesn\u2019t rely on a predetermined structure or framework. The good\nthing about the inductive approach is that it\u2019s a bit more thorough than the\ndeductive approach. However, the approach is more time-consuming than the deductive\napproach. <\/p>\n\n\n\n

So, when should I use the inductive approach to qualitative\ndata analysis? Favor this approach when your knowledge of your research\nphenomenon is very little. <\/p>\n\n\n\n

You now clearly (hopefully) understand the nature of\nqualitative analysis. Now, it\u2019s time to learn how to write qualitative data\nanalysis. <\/p>\n\n\n\n

How to Write Qualitative Data Analysis<\/h2>\n\n\n\n

There are several steps involved while writing qualitative\ndata analysis. Understanding the steps we\u2019re about to discuss will have you\nwriting the data analysis section of your qualitative study pretty fast. Let\u2019s\nnow dive right in and learn how to write qualitative data analysis. <\/p>\n\n\n\n

Convert data into text<\/h3>\n\n\n\n

Before you do anything else, you\u2019ll want to turn all of the data you have into textual form. The other name given for this conversion process is transcription<\/strong>. Now, converting your data to textual form should be pretty easy. Just find the right tool and get it done. EvaSys<\/a>,NVivo<\/a> are two tools we consider particularly powerful. With either of these two tools, you should handle the task real fast. Also, you can perform the transcription job manually. However, doing it manually tends to be tiring and time-consuming.<\/p>\n\n\n\n

Organize qualitative data<\/h2>\n\n\n\n

Now that you\u2019ve your data in textual form, organize it. It\u2019s\nnormal to have vast amounts of data you don\u2019t know what to do with especially\nafter transcription. If you\u2019re not careful, all of the unorganized<\/em> data lying around can confuse or even stress you out.\nThat\u2019s why you should organize your data. <\/p>\n\n\n\n

So how do I organize my data? It\u2019s simple. Revisit your\nresearch questions and objectives and start organizing the data from there. The\nobjectives of your study can greatly help your turn that messy data into\norganized data.  Generate tables and\ngraphs as they\u2019re a great way to organize your data. Also, consider using\nappropriate tools to make the process more efficient. <\/p>\n\n\n\n

Code qualitative data<\/h2>\n\n\n\n

What\u2019s coding your qualitative data? Coding qualitative data\nmeans compressing it into easy-to-understand concepts and patterns.\nEssentially, coding enables you to attach meaning to the field data you\u2019ve\ncollected. <\/p>\n\n\n\n

How do I code my data? Let your study\u2019s objectives guide\nyou. You can code your qualitative data on the basis of the theories they\nrelated to. Also, collected qualitative data gives you hints as to how best to\ncode it. <\/p>\n\n\n\n

Most data analysts prefer the following 3 coding approaches.\nFirst, a data analyst may use descriptive coding. Here, they code data on the\nbasis of the central theme emerging from the dataset. Second, a data analysis\nexpert might prefer In-vivo coding. In this approach, the data analyst lets\nrespondents\u2019 language guide them. Finally, an analyst might identify patterns\nin the data and let those patterns direct them during data coding. You may want\nto research further for other coding techniques you might use for your\nqualitative research. <\/p>\n\n\n\n

Ensure qualitative data isn\u2019t flawed<\/h2>\n\n\n\n

Well, this isn\u2019t exactly a distinct step for how to write\nqualitative analysis. However, we chose to include it given the importance of\ndata validation. Data validation is a method that helps researchers todetermine\nthe accuracy of their methods or research design. Data validation also reveals\nthe extent to which a researcher\u2019s procedures and methods led to consistent and\nreliable results.Shall we say you\u2019vejust learned how to write qualitative data analysis?<\/p>\n\n\n\n

Conclude qualitative data analysis<\/h2>\n\n\n\n

The conclusion of your data analysis<\/strong> is arguably its most important part. So you better make sure this section packs a hefty punch. At this point of the writing process, you must state your findings, linking them to your research\u2019s objectives and questions. After you’ve concluded the data analysis process, you need to craft a final report. <\/p>\n\n\n\n

Qualitative Analysis Report Writing<\/h2>\n\n\n\n

Describe the methods your research relied on and the procedures you performed. But don\u2019t stop there. State the strengths and weaknesses of your study. Next, outline your research\u2019s limitations. Finally, state the implications of your findings while pinpointing a few areas that future research might explore. Here\u2019s a structure<\/strong> your final report might follow: <\/p>\n\n\n\n