If you ever read essay writing reviews at NoCramming, you’ve probably noticed that the comments on essays don’t involve serious stuff. There are mainly details about deadlines, quality, topic, and originality. 

 

As studies progress, such tasks as essays become less and less frequent. Instead, students have to complete new assignments that are graded not only based on the originality or quality of writing in general: 

• courseworks;

• lab reports;

• business plans;

• research papers;

• theses;

• dissertations.

The specifics of such assignments go beyond the words like argumentative/critical/narrative that are usually used to describe a type of essay. Instead, they should follow a well-planned methodology that comprises at least:

• strategy;

• philosophy;

• approach;

• tools for data collection;

• data collection process;

• type of analysis.

When having to choose the type of analysis, students are usually at a loss. They may even choose a random one which even worsens the situation in the end. So, check out the list below to find out the most common types of analysis and when those can be applied.

 

Thematic Analysis (qualitative)

This one is the most popular and frequently misused. It requires to make the following steps: 

• gather all textual information to be analyzed;

• identify recurring words (codes); this is usually done manually by highlighting words and phrases, but software like MAXQDA and NVivo also can help;

• define the main themes by grouping the codes according to similar topics;

• cover all the materials chosen for Results and use several ones in each theme.

So, that's how it should be done. The way it's often done by students is different. The thematic analysis sounds pretty self-explanatory, so many students think they can come up with their own themes. That can be quite subjective at least. At worst, your professor will ask for a coding table (the one where codes and themes identified from each source are presented). 

When to apply:

• interviews;

• qualitative questionnaires (with open-ended questions);

• articles based on previous studies.

Also, thematic analysis often becomes a complementary choice when data is analyzed in a different manner but the thematic subdivision is still required.

 

Doctrinal Research (qualitative)

Doctrinal research may sound unusual, but that’s what law theses are usually based on. However, even an essay writer from https://essaywritingservice.com/pay-for-essay sometimes has to use it to analyze some examples for a law essay. If you need to deal with case law and analyze it based on legislation, that’s the type you should go for. 

 

The main point is, although doctrinal research doesn’t involve calculations and revolves around much factual information, you still need to provide your own insights, conclusions, or criticism. Also, don’t forget about proposing recommendations (e.g. some policies to implement).

 

Statistical Analysis and Descriptive & Inferential Statistics (quantitative)

Descriptive and inferential statistics is a more specific type of statistical analysis. The latter ranges from basic calculations presented using charts and graphs to complex SPSS tests.

It’s applicable in the cases when a researcher works with:

• closed-ended questionnaires and surveys;

• quantitative data from official reports, archives, and articles.

If you need to calculate the mean, mode, and median of a data set, that would be the descriptive and inferential statistics. Such results should be presented in tables.

 

Meta-Analysis (quantitative)

It is used in systematic literature reviews only, purely for articles. The basic criteria are as follows:

• the articles to be covered should be based on quantitative data;

• the articles should be primary;

• the results should include tables, graphs, and charts;

• the visual items mentioned above should combine data from several articles.

Meta-Synthesis (qualitative)

From the name, it should be obvious that this type is related to systematic reviews as well. The requirements are similar to meta-analysis. Yet, the articles in Results should be qualitative only. The Results chapter, in turn, can use the thematic analysis to arrange and comment on the outcomes.

 

Document Analysis (qualitative and, rarely, quantitative)

This one is easier to complete as it has less strict requirements in terms of sources. You don’t have to dig deep into the details of the sample, leave alone methods someone else used. All you need is to gather documents from credible and official sources like Deloitte or the WHO.

 

If you analyze the documents quantitatively, it will be more of a statistical analysis rather than a document one. However, you can go for the combination of two unless your professor is strict. In that case, you will have to stick to only one.

 

Content Analysis (quantitative, qualitative, and mixed)

This is one of the most complex types despite its simple name. The easiest version of content analysis is similar to the thematic one (sometimes, they are just used as synonyms). However, often, it is applied to analyze the data when themes are not enough:

• news;

• photos;

• music;

• films;

• advertisements;

• conversations on social media;

• speeches.

That’s where the quantitative part comes into play. The items or units of information can be calculated to present the most popular patterns, topics, problems, etc. Numerical and textual data is often combined to give a clearer picture of the issue on hand.

 

Takeaway

Remember, when choosing (and writing about) how you will analyze the data, you should be able to visualize the Results chapter. If the analysis you opted for doesn’t give that picture, it means you didn’t settle on anything. Yes, you filled in a subsection in the Methodology chapter with some text, but it probably won’t align with Results.

 

When making the final decision, consider the level of your proficiency for the suggested approach as well as its relevance. No one needs thematic analysis if all you need is to process statistics. And vice versa, there’s no point in promising you would complete SPSS tests for the transcribed interviews.