Qualitative Data Analysis 101 Tutorial: 6 Analysis Methods + Examples

in this video we're going to jump into the often confusing world of qualitative analysis methods we're going to explore the six most popular methods one at a time so that you can make the best choice for your qualitative data analysis we'll also cover some useful tips and tricks as well as some common pitfalls to avoid when you're undertaking qualitative analysis so grab a cup of coffee grab a cup of tea whatever works for you and let's jump into it hey welcome to grad coach tv where we demystify and simplify the oftentimes seemingly bizarre world of academic research my name is emma and today we're going to unwrap the sometimes daunting field of qualitative data analysis methods that is quite a mouthful we will unpack the most popular analysis methods one at a time so that you can approach your analysis with confidence and competence whether that's for a dissertation a thesis or really any kind of research project if you're new here be sure to hit the subscribe button for more videos covering all things research related also if you're looking for hands-on help check out our one-on-one coaching services where we help you through your dissertation thesis or research project step by step it's basically like having a professor in your pocket whenever you need it now if that sounds interesting to you you can learn more and book a free consultation with a friendly coach at www.gradcoach.com alright with that out of the way let's get into it to understand qualitative data analysis we need to understand qualitative data so let's take a step back and ask the question what exactly is qualitative data well qualitative data refers to pretty much any data that's not numbers in other words it's not stuff that you measure using a fixed scale or complex statistics or mathematics so if it's not numbers what is it words you guessed well sometimes yes qualitative data can and often does take the form of interview transcripts documents and open-ended survey responses but it can also involve the interpretation of images and videos in other words qualitative data isn't just limited to text-based data so how's that different from quantitative data well simply put qualitative research focuses on words descriptions concepts or ideas while quantitative research focuses on numbers and statistics qualitative research investigates the softer side of things to explore and describe while quantitative research focuses on the hard numbers to measure differences between variables and the relationships between them if you're keen to learn more about the differences between qual and quant we've got a detailed post over on the grad coach blog i'll include a link below now you might be thinking qualitative is probably easier than quantitative right well not quite in many ways qualitative data can be incredibly challenging and time consuming to analyze and interpret at the end of your data collection phase which takes a lot of time in and of itself you'll likely have pages and pages of text-based data or hours upon hours of audio to work through you might have subtle nuances of interactions or discussions that have danced around in your mind or that you've scribbled down in messy field notes making sense of all of this is no small task and you shouldn't underestimate it so long story short qualitative analysis can be a lot of work don't stress though in this video we'll explore qualitative data analysis qda for short by looking at the six most popular analysis methods these qda methods can be used on primary data data you've collected yourself or secondary data data that's already been published by someone else so without further delay let's get into it right let's start by outlining the analysis methods and then we'll dive into the details for each one the six most popular qda methods or at least the ones we see at grad coach are number one qualitative content analysis number two narrative analysis number three discourse analysis number four thematic analysis number five grounded theory and number six ipa if that all sounds like gibberish don't worry we will explore each of them in this video so let's do it first up is a qda method called qualitative content analysis or just content analysis for short content analysis is possibly the most common and straightforward qda method at the simplest level content analysis is used to evaluate patterns within a piece of content for example words phrases or images or across multiple pieces of content or sources of communication for example a collection of newspaper articles or political speeches with content analysis you could for instance identify the frequency with which an idea is shared or spoken about like the number of times a kardashian is mentioned on twitter or you could identify patterns of deeper underlying interpretations for instance by identifying phrases or words in tourist pamphlets that highlight india as an ancient country because content analysis can be used in such a wide variety of ways it's important to go into your analysis with a very specific question and goal or you'll get lost in the fog with content analysis you'll group large amounts of text into codes summarize these into categories and possibly even tabulate the data to calculate the frequency of certain concepts or variables because of this content analysis provides a small splash of quantitative thinking within a qualitative method naturally while content analysis is widely useful it's not without drawbacks one of the main issues with content analysis is that it can be very time consuming as it requires lots of reading and re-reading of the text also because of its multi-dimensional focus on both qualitative and quantitative aspects it is sometimes accused of losing important nuances in communication content analysis also tends to concentrate on a very specific timeline and doesn't take into account what happened before or after that timeline this isn't necessarily a bad thing though just something to be aware of so keep these factors in mind if you're considering content analysis every analysis method has its drawbacks so don't be put off by these just be aware of them right let's take a look at the next qda method narrative analysis okay next in line we have a powerful qualitative analysis method called narrative analysis as the name suggests narrative analysis is all about listening to people telling stories and analyzing what that means since stories serve a functional purpose of helping us make sense of the world we can gain insights into the ways that people deal with and make sense of reality by analyzing their stories and the ways they're told you could for example use narrative analysis to explore whether how something being said is important for instance the narrative of a prisoner trying to justify their crime could provide insight into their view of the world and the justice system similarly analyzing the ways entrepreneurs talk about the struggles in their careers or cancer patients telling stories of hope could provide powerful insights into their mindsets and perspectives in other words narrative analysis is about paying attention to the stories that people tell and more importantly the way they tell them of course the narrative approach has its weaknesses just like all analysis methods sample sizes are generally quite small due to the time-consuming process of capturing narratives because of this along with the multitude of social and lifestyle factors which can influence a subject narrative analysis can be quite difficult to reproduce in subsequent research this means that it's difficult to test the findings of some of this research similarly research bias can have a strong influence on the results here so you need to be particularly careful about the potential biases that you can bring into your analysis when using this method nevertheless narrative analysis is still a very useful qualitative method just keep these limitations in mind and be careful not to draw broad conclusions all right let's take a look at the next qda method discourse analysis number three on the list is discourse analysis discourse is simply a fancy word for written or spoken language or debate so discourse analysis is all about analyzing language within its social context in other words analyzing language such as a conversation a speech etc within the culture and society it takes place in for example you could analyze how a janitor speaks to a ceo or how politicians speak about terrorism to truly understand these conversations or speeches the culture and history of those involved in the communication is important for example a janitor might speak more casually with the ceo in a company that emphasizes equality among workers similarly a politician might speak more about terrorism if there was a recent terrorist incident in the country so as you can see by using discourse analysis you can identify how culture history or power dynamics to name a few have an effect on the way concepts are spoken about so if your research aims and objectives involve understanding culture or power dynamics discourse analysis can be a powerful method because there are many social influences in how we speak to each other the potential use of discourse analysis is vast of course this also means it's important to have a very specific research question or questions in mind when analyzing your data and looking for patterns and themes or you might end up going down a winding rabbit hole discourse analysis can also be very time consuming as you need to sample the data to the point of saturation in other words until no new information and insights emerge but this is of course part of what makes discourse analysis such a powerful technique so keep these factors in mind when considering this qda method right so far we've covered content analysis narrative analysis which analyzes stories and discourse analysis which analyzes conversations and interactions next up we've got thematic analysis which focuses on themes and patterns let's jump into that thematic analysis looks at patterns of meaning in a data set for example a set of interviews or focus group transcripts but what exactly does that mean well a thematic analysis takes bodies of data which are often quite large and groups them according to similarities in other words themes these themes help us make sense of the context and derive meaning from it let's take a look at an example with thematic analysis you could analyze 100 reviews of a popular sushi restaurant to find out what patrons think about the place by reviewing the data you would then identify the themes that crop up repeatedly within the data for example fresh ingredients or friendly wait staff so as you can see thematic analysis can be pretty useful for finding out about people's experiences views and opinions therefore if your research aims and objectives involve understanding people's experience or view of something thematic analysis can be a great choice systematic analysis is a bit of an exploratory process it's not unusual for your research questions to develop or even change as you progress through the analysis while this is somewhat natural in exploratory research it can also be seen as a disadvantage as it means that the data needs to be re-reviewed each time a research question is adjusted so basically thematic analysis can be quite time consuming but for a good reason so keep this in mind if you choose to use thematic analysis for your project and budget extra time for unexpected adjustments right let's hop on to the next qda method of choice grounded theory all right it's time to get grounded well kinda grounded theory is a powerful qualitative analysis method where the intention is to create a new theory or theories using the data at hand through a series of tests and revisions for example you could try to develop a theory about what factors influence students to watch a youtube video about qualitative analysis the important thing with grounded theory is that you go into the analysis with an open mind and let the data speak for itself rather than dragging in existing hypotheses or theories into your analysis in other words your analysis must develop from the ground up hence the name in grounded theory you start with a general overarching question about a given population for example graduate students then you begin to analyze a small sample like five graduate students in a department at a university ideally this sample should be reasonably representative of the broader population you'd then interview these students to identify what factors led them to watch the video after analyzing the interview data a general hypothesis or pattern could emerge you might notice that graduate students are more likely to read a post about qualitative methods if they are just starting on their dissertation journey or if they have an upcoming test about research methods from here you'll look for another small sample maybe five more graduate students in a different department and see whether this pattern or this hypothesis holds true for them if not you'll look for more commonalities and adapt your theory accordingly as this process continues the theory develops what's important with grounded theory is that the theory develops from the data not from some preconceived idea you need to let the data speak for itself so what are the drawbacks of grounded theory well some do argue that there's a tricky circularity to grounded theory for it to work in principle you should know as little as possible regarding the research question and population this helps you reduce the amount of bias in your interpretation however in many circumstances it's also thought to be very unwise to approach a research question without knowledge of the current literature so basically it's a bit of a chicken or the egg situation regardless grounded theory remains a popular and a powerful option it can be a very useful method when you're researching a topic that is completely new or has very little existing research about it it allows you to start from scratch and work your way from the ground up right time for us to move on to the final qualitative analysis method ipa let's jump into it interpretive phenomenological analysis ipa okay no let's just stick with ipa okay ipa is designed to help you understand the personal experiences of a subject for example a person or a group of people concerning a major life event an experience or a situation this event or experience is the phenomenon or phenomena that makes up the p in ipa these phenomena may range from relatively common experiences such as motherhood or being involved in a car accident to those which are extremely rare for example someone's personal experience in a refugee camp so ipa is a great choice if your research involves analyzing people's personal experiences of something that happened to them it's important to remember that ipa is subject centered it's focused on the experiencer this means that while you'll likely use a coding system to identify commonalities it is important not to lose the depth of experience or meaning by trying to reduce everything to codes also keep in mind that since your sample size will generally be very small with ipa you often will not be able to draw a broad conclusions about the generalizability of your findings but that's okay as long as it aligns with your research aims and objectives now another thing to be aware of with ipa is personal bias while researcher bias can creep into all forms of research self-awareness is critically important with ipa as it can have a major impact on the results for example a researcher who was a victim of a crime himself could insert his own feelings of frustration and anger into the way that he interprets the experience of someone who was kidnapped so if you're going to undertake ipa you need to be very self-aware or you could muddy the analysis keep these limitations and pitfalls in mind and you will have a powerful analysis tool in your arsenal all right so there we have it the six most popular qualitative data analysis methods that we work with here at grad coach so at this point you're probably asking yourself the question how do i choose the right one well selecting the right qualitative analysis method largely depends on your research aims objectives and questions in other words the best tool for the job depends on what you're trying to build for example perhaps your research aims to analyze the use of words and what they reveal about the intention of the storyteller and the cultural context of the time perhaps your research aims to develop an understanding of the unique personal experiences of people that have experienced a certain event or perhaps your research aims to develop insight regarding the influence of a certain culture on its members as you can see all of these research aims are distinctly different and therefore different analysis methods would be suitable for each one also remember that each method has its own strengths weaknesses and general limitations no single analysis method is perfect so it often makes sense to adopt more than one method this is called triangulation but this is also quite time consuming as we've seen these approaches all make use of coding and theme generating techniques but the intent and approach of each analysis method differs quite substantially so it is really important to come into your research with a clear intention before you even start thinking about which analysis method or methods to use start by reviewing your research aims objectives and research questions to assess what exactly you're trying to find out then select a method that fits never pick a method just because you like it or have experience using it your analysis method or analysis methods must align with your broader research aims and objectives okay so let's quickly recap on the six methods firstly we looked at content analysis a straightforward method that blends a little bit of quant into a primarily qualitative analysis then we looked at narrative analysis which is about analyzing how stories are told next up was discourse analysis which is about analyzing conversations and interactions then we moved on to thematic analysis which is about identifying themes and patterns from there we went south with grounded theory which is about starting from scratch with a specific question and using the data alone to build a theory in response to that question and finally we looked at ipa which is about understanding people's unique experiences of a phenomenon now of course these aren't the only approaches to qualitative data analysis but they are a great starting point if you're just dipping your toes into the waters of qualitative research for the very first time if you do want to learn about other qualitative data analysis methods drop us a comment below if you enjoyed the video please hit the like button and leave a comment if you have any questions if you are in the process of writing your dissertation thesis or any other research based project be sure to subscribe to the grad coach channel for more research related content and lastly if you need a helping hand with your research check out our private coaching service this is where we work with you on a one-on-one basis chapter by chapter to help you craft a winning dissertation thesis or research project if that sounds interesting to you book a free consultation with a friendly coach at www.grad.com as always i'll include a link below and that's all for this episode of grad coach tv until next time good luck you

Channel: Grad Coach

Views: 58,248

Rating: 4.9555554 out of 5

Keywords: qualitative data analysis, qualitative analysis, qualitative data analysis methods, content analysis, thematic analysis, discourse analysis, grounded theory, IPA, qualitative research, qualitative methods

Id: j9A3ceOBihM

Length: 25min 25sec (1525 seconds)

Published: Wed May 12 2021