Welcome to my youtube channel which is titled research methods class with dr lydia wabogo in research methods we have a book titled research methods theory and practice this book is accessible through the website where you can access the hard copy of the book or a downloadable pdf format of the book in the same website you are able to access all the courses which includes the free research methods course ibm spss statistics course m and e consultancy course which are available at a fee please find the links in the description welcome welcome to this lesson where we are going to look at data analysis technique and concentrate on how to analyze qualitative data in our previous lesson we have looked at how to present section 3.8 when you have quantitative data so this lesson will concentrate on qualitative data which we have said we use inductive or thematic analysis to analyze qualitative data so we are still discussing section 3.8 of the uh of chapter 3 of the research proposal at the end of this lesson you should be able to discuss qualitative data analysis explain the steps that you follow when you are conducting qualitative data analysis and explain the requirements of section 3.8 when you are presenting qualitative data again please remember we discussed data analysis techniques in details in lesson 46 to lesson 50. so again we are still in chapter three now we are in subsection 3.8 which we have divided into two the previous lesson has looked at quantitative data now we are looking at qualitative data we have also said in our previous lesson that it is your responsibility to make the data that you collect from the field meaningful and this process of making your data meaningful is what is referred to as data analysis and the method of data analysis is determined by the type of data that you collect and the scale of measurement and that is why we have said numerical data all quantitative data is analyzed using statistical methods statistics then you have narrative data or non-numerical data is analyzed using uh thematic or inductive uh thematic method and we have also said in both of them you may use software like spss and and vivo for narrative for numerical and narrative respectively now when we talk about qualitative data we are talking about data that you collect in a numeric form it consists of detailed descriptions of situations events people interactions and observed behavior so qualitative data is in form of words and observations videos and pictures and not in numbers it also consists of direct quotations from people about their experiences their attitudes their beliefs and their thoughts common examples of qualitative data we have interview transcripts documents for instance report minutes of meetings emails etc we have field notes we have video we have audio recordings and images now this type of data is not converted into numerical form but it is presented verbatim as it were collected from the field by the researcher whereas in quantitative analysis data analysis begins after data collection in qualitative research data analysis is tied to data collection and it occurs throughout the data collection process why do you analyze data immediately you collect it in qualitative research is so that you discover categories and themes and to be able to develop theories you so you do not want to put to leave it for a long time where you are going to forget what your respondents may have told you so we mainly analyze it immediately after collecting so that our memory is still fresh on the situation or the environment that we had visited and what your respondents mentioned or told you about the phenomena that you are investigating there are various methods of analyzing qualitative data one of the common one is the inductive method or thematic inductive method and this is the one that we are going to discuss because these steps are the ones that you need to put in your subsection 3.

8 if you have qualitative data in your research study so we when we are analyzing qualitative data we follow four steps the first one is called processing condensed data which is also referred to as pre-analysis of data this step involves transcribing interviews that is when you change them from audio to print and translating observed events and behaviors into words so you can see this is not something that needs to wait if you have to translate what you observed it cannot wait for a week or two or a month it must be done immediately you leave the site or if you're able to do it in the site once you have collected data regarding your phenomena so that is the first one the second one is condensing data and this is done by doing five things the first one is editing this is where you remove any grammatical error in your data to ensure precise explanation in very concise form and also increase quality please note when you are editing do not lose the critical meaning of the data do not change the meaning of your data meaning what your respondents told you do not lose it you are only editing data by removing grammatical errors so that there will be flow and it will be clear however we remove ambiguity this involves qualifying the meanings presented by the data qualifying the meaning for instance if your respondents keep repeating a phrase then that becomes monotonous and that is what you need to remove that is an ambiguity so this repetitive phrase or statements needs to be removed for instance if you ask your respondents you are conducting an interview and the respondent keep saying ah and then every response must have the ah and take some time before they respond initially they are may have shown something but if it keeps on recurring then it becomes monotonous and therefore when you are removing ambiguity this is what you are going to remove please do not change the meaning of the data so once you have edited you have removed ambiguity you then create data categories a data category is a theme or class of data established to represent related or similar forms of data this is where you establish the theme that is emanating from the data that you have collected you may have collected done an interview or conducted an interview for one hour regarding a phenomena or regarding a particular variable so your respondents moved from one story to the other from one incident to another related to that phenomena so as you transcribe and edit and remove uh ambiguity then you are able to fit in story that came in maybe let's say minute 50 that it defeats in the theme that was discussed in minute one and ten so that you are able to do and you identify data categories of course these data categories are informed by your problem and also from literature and the theories once you create the data categories then you assign data to the established categories using codes so you have a data category let's assume one of the data category is called divorce then you bring in any information regarding the divorce that was discussed by your respondents and you are translating it verbatim you are transferring it to this category verbatim and we have discussed this in in details in lesson 28 then you summarize the data in each category where the researcher as a researcher you should condense and report verbatim what the respondents reported regarding your phenomena then that is step two step three is presentation of findings in qualitative research we use tables that are called interpretive frames or analytic frames we don't use statistical tables like frequency distribution tables or cross tab so how do you present now the findings you have already now identified the categories you have fitted in the words or the verb as verbatim as you are given by your respondents then now you present your data either in continuous prose or in interpretive frame once you present the data then you make sense of it this means interpreting the data and then drawing parallels and disparities from the theories that you had reviewed so this helps you to make conclusion and recommendations for your study so they are very similar to how you would do it in quantitative so once you have pre-analyzed the data then you condense it then you present the data and you make sense of it and these are the steps that you mentioned in section 3.

8 as long as you have quantitative data so you explain how you will pre process your data how you will condense it then how you will present the findings and make sense of it and do not forget to explain the role of qualitative data in your study why do you need to have it why why do you need to have qualitative data now if your study was mixed method you have both quantity and quality always remember we start with quantitative data starting with descriptive statistics then inferential and then you bring in qualitative data to corroborate the quantitative findings and that brings us to the end of this section we have discussed how to analyze qualitative data our next lesson will focus on section 3.9 of chapter 3 of the research proposal which is on ethical issues do not forget to subscribe to this channel like and share this lesson with your friends and any question that you have regarding today's lesson feel free to put it on the comment section.