# Qualitative Research Data Analysis

**Channel:** Chanell Jan Concepcion
**Source:** https://www.youtube.com/watch?v=oZgP5ZFvyF4
**Transcript page:** https://www.withtranscript.ai/video/oZgP5ZFvyF4

## Chapters

- 0:02 — Overview of Qualitative Data Analysis
- 9:31 — Coding Methods and Practice Examples
- 21:02 — Advanced Coding and Data Management
- 30:27 — Themes, Traditions, and Interpretation
- 38:50 — Generic Analysis and Closing Discussion

## Transcript

**[0:02]:** good morning everyone we are in module eight which is qualitative um data analysis and i'm dr chanel ponson from siliman university college of nursing so we will talk about qualitative data analysis the whole process coding qualitative data management analytic procedure and the research tradition and analysis now we have to understand that there are different sources of qualitative data it could be from your verbatim transcripts from your interviews that means you have to write them word for word from your focus group discussion from your diaries and from your observational notes so let's just take a look on the overview of qualitative data analysis we have to know what are the purposes of data analysis in qualitative research first because we have volumes and volumes of data we need to make sure we know how to organize it and provide a structure and get meanings from those data we have to understand also that data analysis and

**[1:16]:** qualitative research sometimes is done in conjunction or concurrently with data collection so you do data collection you analyze and then you also collect data at the same time it can be okay that that's pretty flexible and then you have to look at the patterns and concepts um that uh that emerge even starting during data collection so my experience in qualitative data collection is that it's fun but it's also labor intensive and lots of hard work you have to employ critical thinking and you have to be creative think outside the box and you should be able to know what are the resources available to you including the software and computers and other things that you need i have to warn you it's fun but it's that also has a lot of challenges first is there are no universal rules for analyzing qualitative data sometimes there are authors that we give you guidelines uh depending on the

**[2:18]:** research tradition and its philosophy but it's pretty much flexible okay because there are a lot of data that you have from your transcripts from your interviews from your observational notes from your field work you need to have a good strategy and sometimes reducing the data is a struggle because you are collecting very rich data but you need to be able to present it in understandable ways so these are some decisions that you have to make when you are analyzing qualitative data who will do the analysis is it only you or with a theme but with a team but you also need to know that you have to make sure that you enhance rigor now trustworthiness and who will transcribe do you need to do it yourself or you get another person who was not there in the interview to transcribe it usually um i like to transcribe it in my own because it's my way

**[3:14]:** of immersing myself into the data but sometimes you just don't have time so i would usually hire somebody to help me transcribe but i would still go and look at the transcription and compare it with a recording to make sure it's accurate so will the coding and analysis be inductive is it going to be bottoms up or top down okay using a framework or pre-existing coding and you just kind of plug it in it could be worrisome but it's a very productive way to do it some qualitative researchers do it this way how much data should be coded is just the important points or do you have to code everything i would really suggest to do everything so that you will not miss out on the important parts in your data will you focus on actual words description and action or the meaning the underlying meaning and latent um meaning latent content searching for underlying

**[4:08]:** ideas and concepts and what will be your product is it theories is it model are these themes that you need to produce to describe the phenomenon for example what about the computer do you need to use computer software or do you do it manually you also need to know data analysis involved do you need to count the numbers or most participants many participants maybe you can use word cloud such as this this is barack obama's inaugural address and there are free um websites that can do uh word clouds for you and in vivo has that feature as well okay let's just skip that will you also uh use formal guidelines such as this is the collision method for example collision is very straightforward in detailing what needs to be done in terms of the analysis so for collisi you need to write out the verbatim transcripts and then you identify the significance statement and then

**[5:10]:** from the significant statement there are formulated meanings and then you aggregate it you can create categories clusters and themes around those and then you integrate the ideas and then you come up with an exhaustive description of the phenomenon based on the themes of clusters cluster of things that you have done and then you have a formal structure and you need to have a member check you go back to the participants and validate the exhaustive description and the fundamental structure of the phenomenon that you're describing so you can see here there's significant statements and that each of this needs to be located at a certain point in your transcripts mon hall has the stepwise approach step wise because it doesn't have to be one two three four you can go back and forth these are just guidelines first is you have to immerse yourself in the data and you have to know what is the aim

**[6:03]:** the phenomenological aim of your study and then you do an existential inquiry expression and processing so this is now your analysis and then you have because this is hermeneutic in nature phenomenological contextual processing and then you interpret and then you write the phenomenological narrative language is really important in doing phenomenological study and presenting and analyzing the data then mannin also has a textual analysis conducting thematic analysis holistic and centralized approach for example you see the whole sentence look at the themes there or maybe you just select and highlight certain points or you can do a more detailed line by line approach after that you identify things and then then has like one whole chapter about what themes are it's a representation of the meaning or interpretation of a certain phenomenon or you can also choose you can also choose an illuminating phrase or data to capture the meaning of the theme this is also then

**[7:08]:** managed interview the transcription you transcribe the text layers and back and forth like a hermeneutic circle until you know a conversation a dialogue with your text read and reread the transcribed text while listening to the audio tape you do selective or highlighting approach and you can also use your own analysis matrix okay so what is the process of data analysis data analysis could be complex it's creative it's iterative and non-linear because it's not just like one way one direction sometimes you can you can uh vary the process here so this is just a general process of what happens during qualitative analysis so you need to have intensive readings some people have some researchers have pre-coding already based on the theory or concept map or framework that they use you do segmenting you do know coding labeling of the themes and then you kind of recode it again refine it regroup it resort it categorize it

**[8:13]:** and in the end you can have synthesizing interpreting and theorizing not all qualitative research go through this process but like you said it's more flexible and not all the outcomes would be a theory or model or a um or these it depends on what is your the aim of your study and what is the research tradition that you are using so this is just like um data analysis process like you have data collection and sometimes you have to you know condense the data you have you have to go back and forth and you can see that it is definitely non-linear in terms of analyzing the data what's important is in the beginning you have to really immerse yourself in the data and many qualitative researchers use memoing analytic memory this writing the thoughts and observations and reflections on the data so this is an example you can see that the writer here the researcher here

**[9:11]:** writes out his thoughts and this is part of your uh reflexive liberty is sometimes it all be also part of your data analysis so given the non-prescriptive nature of most qualitative analysis it may be said that it is a process learned best by doing it

**[9:31]:** the data analysis activity could be categorized or could be described into three concurrent flows so you have condensation of the data where you select focus simplify abstract and transform the data you present it in a more organized compressed assembly of information it could be you know you could draw some conclusions from it through matrices graphs charts networks and you have to draw conclusion or you verify those data now let's go to coding now in coding let's just backtrack a little bit and look at what codes are it's used to identify um interesting salient invocative and essential features of the data in relation to the phenomenon under investigation okay it's taken from data segments such as a phrase sentence and a paragraph so this is for example this is part of what's called this a data transcript and then you are able to code here the mod the code here you can see it's motivation okay

**[10:38]:** so there's no straightforward guideline developing codes and there's no magical number okay in terms of how much you should code or how many codes you have to come up with so these are most uh of the common ways of coding elemental methods that provide foundation to coding descriptive in vivo process concept and holistic coding let's look at this one by one so you have descriptive coding usually a lot of the beginner researchers researchers use this these are using nouns but it does not provide insight into the meaning you're just kind of labeling it for example you're excerpting your transcript would be the other day we ran out of everything and we had to go to church and get food so you're coding there is that you're using the food pantry or food pantry use so that's your descriptive coding okay for in vivo is you use the words or short phrases from the participants own

**[11:37]:** language and the data recorded as code so it's more kind of literal verbatim um coding okay so you use usually you use this you don't know how to label it you just use their own words of the respondents so the same excerpt and your code would be a run out of everything had to go to church and get food okay so in vivo you're using quotes from from the respondents process coding this is a coding method that uses gerond or just record this on the computer okay all right so so for example here coping with the risk of hunger all right so this is your code concept coding right holistic coding involves using codes to grasp broad ideas in large chunks of data rather than coding smaller segments okay so for example you're saying um you know this is like the whole not just one sentence the whole the whole uh narration and then your

**[12:43]:** concept would be this is the food management strategy okay so you're looking at in chunks of data not just looking at small segments in detail okay so all right let's have a um a exercise here and what i want you to do is you go to your chat box okay i will give you certain data extracts and i want you to use try to read through it and give me your code there's no wrong answer just try to see what would be your coding for this different data okay let's let's go first okay all right so let's do a descriptive coding this is your data and put in your chat box what you would code this for so it says i walked towards the school there was a 7 11 convenience store one block away next to a small professional office building an optometrist podiatrist another medical health related clinic directly across the street was

**[13:44]:** an empty lot but next to stood a burger king restaurant okay try to look at the chat box and i want you to write what is your code for this description okay i'll wait what would be your code just it could be one word or it could be a sentence okay anyone okay proximity good all right celine says proximity what else what else do you have in mind directions dr bersinia good what else i wanted to see everyone's commercial space frenzy great what else do you have

**[14:36]:** others are still thinking or still connecting i don't know commercial space what else put in the chat box

**[14:49]:** come on come on

**[14:53]:** businesses block okay good map location block survey great observation upon walking that's wonderful location great

**[15:08]:** aha wonderful so you see you have different codes for this just you know one one statement or a few statements from from the respondent but you have different codes that you have identified here okay street mapping good all right directions location good wonderful okay distance all right so in the book what they wrote is businesses okay so it doesn't mean your other codes are not right it's just navigation that's okay position um it could be businesses establishments right wonderful okay let's have another one okay i want you to read this try to do an in-vivo coding that means you're using the participants words to describe what he means by this so he said i hated school last year freshman year it was awful i hated it and this year's a lot better actually i um i don't know why i guess over the summer i kind of stopped caring about what other people thought and

**[16:18]:** cared more about just i i don't know okay so what would be your in vivo coding for this transcript put in the chat

**[16:34]:** box

**[16:38]:** what do you think in vivo again in vivo using words okay what do you think are the words that you could cat that would capture okay hated school wonderful all right stop caring about what other people thought good hated school last year kind of stopped caring hated school that's kind of hated school last year great wonderful okay all right looks like we hated school i don't know i like that i don't know okay great stopped caring all right what's this some kind of projection maybe it looks like it's so familiar i hated going online i hate this zoom session all the time freshmen is awful okay can't relate right dr vilsenia okay great so see you have you're able to capture using you know the the participants words to describe to code your data all right so that could be another way you have to remember that you can do a mix and match too

**[17:46]:** okay if you want to do description here or in vivo here or something a process coding here great so in the book uh it says here hated school just like what you do this year's better stop caring you have captured it exactly as awful i like that uh i like that word awful okay so that's great okay let's do more of a process coding okay say process you're looking at more like uh doing ing okay geront okay so this is the data well that's one problem that my school is pre is pretty small so so i so if you say one thing to one person and then you decide to tell two people then those two people will tell two people and one period everybody else knows everybody in the entire school knows that you said whatever it was so okay so try to do a process coding again you can use gerons here words

**[18:50]:** that end and ing okay let's see what you got

**[18:59]:** okay kayla gossiping wonderful there he says telling people wonderful what else spreading mark says spreading spreading rumors good spreading information all right telling good wonderful all right gossiping across school good what else communicating i like that gossiping sharing good talking wonderful disseminating sounds so social but you know circulating i like that telling people good all right wonderful okay gossiping that like looks like that's occurring most of the time you can see that you can the patterns are kind of uh you know there's uh relaying and like passing on complaining okay all right spreading rumors so um the book says just like what you said spreading rumors knowing what to say or gossiping just like you said right okay so you can also do a um kind of thematic statement in phenomenological studies saldana who also included the book with miles and huberman on qualitative data analysis said that especially those with phenomenological research label and

**[20:31]:** analyze portion of the data with an extended thematic statement rather than a shorter code so most of the time if you're doing a phenomenological studies it's not just one code usually you would extend it into more of a theme right like for example gossiping or relaying message to other people that could be what you would label it he refers to this type as a type of coding as themes or theming the data or identifying themes okay

**[21:02]:** so other ways to do it you could use the effective methods effective would be more like emotions values uh evaluation coding okay all right let's try it let's try this okay try to see what is the emotion if you wanted to do like capturing the emotion of that person okay and this is the day that you got i just hated it when he got awarded with honor i mean we're praising mediocrity here never mind that what what you're accomplish isn't worth with squat it's all about who you know in the good old boys network okay try to see what is the emotion you think you could use to code this this data let's see jealousy hatred good envy frustrated wonderful bitterness very good all right bitterness is coming out insecurity frustration about the system hate hatred hatred and bitterness wonderful great so um hated it bitterness this is um the coding that

**[22:14]:** you can get frustration resentment hate dismay disappointment see you can you're able now to code uh this data using the emotion coding very good now you could be qualitative data and uh analyzers all right you could also do values coding for example you're looking at more like evaluative or you're looking at the responses of people so for example you're talking about government regulation government control convert religious motives um you know all of these things you can you can look at the value depending on the uh the research question or the purpose of your study okay you can also do evaluation coding like for example you're talking about the artist in residency program right successful qualified integration all of these kinds of things okay there's also literary and language method you can see here this is a different way of coding you can see here that um you are trying to really look at conflicts you

**[23:17]:** would label it as con c-o-n if it's a tactics it's tac attitude so there's like um certain letters that are um that would code what kind of um what kind of thing that you wanted to see so you can see here you know uh we're talking about conflicts so it's resources emotions it's frustration and all of this okay you don't have to do this every time but there are some researchers that wanted to use this so that it's easier for them to to group later on these uh this codes or this data okay so you can also do an exploratory method more holistic provisional hypothesis okay so you're looking for example at these um transcripts and you would uh do it as like the guard prescription method naked patches all of these kinds of things you're looking at not just in a sentence but as a whole okay so this is what you call exploratory

**[24:14]:** method okay so you can see here now you'll have an idea now um how to do coding okay so question is that how do we how do we manage the qualitative data okay so coding and data management so after you have to code you have to also manage the data so coding converts the data into smaller more manageable units so when you're coding you're actually already managing the data now you have to make a decision whether you have to do it manually or you have to do computer software okay so manual methods there's so many types of um manual methods here you could do physical photos you can break it down you can do it different folders you can cut some of the excess of the data highlight it use color coding post it and many other methods okay this is an example maybe you want to do highlighting sometimes because there are so many

**[25:14]:** codes you run out of colors you know you try to mix and match colors this could be one thing but you can see here um the yellow represents you know there's always one portion in your uh in your data or your paper where you can put the codes in all right you can do this in word you can do this in excel or you can also do this using your nvivo or your other computer so this could be another one you can use this is one example of what a matrix is all about so for example you can you can uh here on the right the rightmost side are the statements but you kind of get going a different direction other people would also put the statement first and then looking at the theory of the themes and then you can categorize or code the data in another um in another column so you can

**[26:05]:** do it this way right or if you're done all of the coding you can organize it so you can put all the greens all the blues in different uh categories or different columns okay this is an example of a of a researcher uh doing coding and using post it color coding to analyze the data this is okay but sometimes when you're about to present the data you know it's a little bit problematic but some people do this and you can see here and this is what i did i did not have any software i don't know how to do software and i did my dissertation i would do a lot of cutting i printed cut it and then try to categorize it in different sessions this is like me how many years ago some people would also like to do this and then this there's a margin here and then you can put all your

**[26:56]:** codings or your initial codings right here okay that's manual you could also do it in um in word you can see just using word but you can do the new comment right here and then you can do all the the different uh codes here on the side okay so this is what how you can do your qualitative data analysis if you want to do line by line there's a way that you can put them in lines and then you can put numbers in it and then you can put all your codes in one column okay this is a line by line sentence by sentence method of coding of course there are a lot of software that are available but most of the software you need to buy okay like in vivo there's a student version of in vivo some of my phd students were able to buy they were able to do in vivo 12

**[27:50]:** i think which cost them about 6 000 pesos not bad i think you have very limited access to it but you can do a free trial which is good for i think 14 days or less than 30 days and then um if you you know some of these could cost hundreds or tens of thousands if you need to buy it but the student version is is much cheaper but you have to really show them that you have the id and things like that okay i'm uh i usually teach en vivo to my phd students like dr bilsinia remember doing the nvivo um i still remember okay so i'll just give you a little bit of sense of what nvivo can do this this is not very comprehensive but just to give you a overview of what it is since 1981 and vivo has been the leading provider of qualitative data analysis software now in vivo

**[28:48]:** 12 is more comprehensive oh my god what is what is going on let me just what is going on it's not very nice it's loading kind of loading okay let me share it through just a moment okay let me share this one instead okay

**[29:16]:** this might be better okay leading provider of qualitative data analysis software now in vivo 12 is more comprehensive and more powerful than ever before you know your research best with in vivo you retain control over your data supporting the widest range of disparate data sources and vivo supports your methodology whether you're doing a literature review a dissertation or a mixed method study to analyze your data you can choose from total control with no automation to autocoding and refining large data sets you'll confidently explore and question your data with the widest range of visualizations in the market with nvivo 12 you'll have more time with your data more onboarding tools that will bring you up to speed with the software quicker and vivo powerful research made easier yeah definitely powerful research made easier but also you need to spend money to buy it okay so let me go back to my powerpoint

**[30:27]:** so analytic procedures so again you have to identify broad categories codes and clusters and we talk about using themes and we have to remember that themes are abstract entries that bring meaning and ident identity to a current experience and it's variant manifestation so themes can capture and unify the nature or basis of experience into a meaningful whole okay so there are some questions that you also need to consider in the code sometimes when you get into your data you say okay what do i do now just identify or what you have to remember that the first thing you need to know is what am i researching what is the goal of my study what is my research question that's very central and you have to keep it in your mind as you do the coding so you would think what are what are the people doing here what do i see what's going on here

**[31:22]:** what are we trying to accomplish you know what is these are questions that you need to to uh put in your mind as you code so it's not just any code for for for that matter you have to be more purposeful or intentional in in doing your coding so this is an example of how you can crunch or you can categorize so for example these are all the statements in the first uh in this first column and then you're able to look at the codes and they share the same codes and maybe you can cluster them together and say this is agonizing over what should have been okay so this is the theme that's emerging from from your data so now you're doing reduction right okay and you can do thematic analysis when you do that you can look at similarities contrast maybe commonalities are there natural variations what are the patterns here how do

**[32:18]:** i interpret for example if somebody just says oh i'm fine but of course somebody died you have to just not look at what is said but you have to look at what is unsaid you have to look at the context this is part of for example interpretive or hermeneutic phenomenology integrating themes or categories into integrated description models or theories okay so you can see here all the data you do the codes and then you categorize and then you cluster them together in themes or concepts or subcategories and then you have your themes assertions description or your theory if that is uh it's for example you're doing a grounded theory okay so let's look at we have a few more minutes left but let's look at some of the research traditions each of a research tradition have their own kind of uniqueness in terms of data analysis we don't have to go through this um you

**[33:11]:** can you can read the pdf file if you want to to look at this for example an ethnographic study of 12 likes bradley was giving us 12 sequences of how you do ethnographic analysis if you do ethno nursing for example linen girl also has prescriptions or guidelines not prescriptions maybe guidelines on how to analyze data okay if you do a phenomenal logic study for example a descriptive study i talked to you about calisi so collision has this guideline if you use georgie as your um your underlying uh methodology this is also what they uh the guidelines are orvan camp right okay uh this is an example of collidesy so you can see here this is the formulated meanings and there are theme clusters and then the emergent themes are are identified here so sometimes you have a first theme and then you re-analyze it again you could uh transform it into second theme sometimes you

**[34:13]:** also need to re-label your themes that would really describe what the experience is all about okay so this is just an example for van maanen we talked about the textual analysis for van maanen van manen you could also use um use the live worlds or life worlds uh but man in my study i just used four life worlds but in his his latest book on phenomenology of practice if you want to read it i i can give you the the the book uh the ebook he included another a dimension which is liv thinks so what he's saying is one man says that if you're describing an experience or interpreting an experience it's usually in the context of these dimensions in the life world for example lived body okay that's corporeality lived time temporality lived space spatiality lived uh human relations that's relationality and he added another dimension of live things or materiality let's just say

**[35:12]:** we're doing this zoom session for example okay what is our lived body sometimes it's so uncomfortable because he has to sit here that's my experience right or i'm just talking to myself i see my video here and looks like all of you are quiet and only dr belcini is talking to me that seems like i'm so uncomfortable so that's your experience in your in your body like i wanted to go to the bathroom but i can't because i have to get stuck here and finish my my my lesson for example live time time sometimes when you are doing a synchronous session one hour is a bit too long don't you think i'm already almost like one minute before 12 o'clock or space what does the space look like it looks like here's supposed to be so really lively when it's a face-to-face um you know uh teaching but now it's like i'm isolated right or

**[36:01]:** your relations yes you can talk to your classmates but it's different when you do a facebook i cannot hug people or i cannot talk to them i can't touch them um they're you know there's there's physical distancing there's social distancing but it just feels different when you're just talking to somebody in zoom for example lyn thinks i cannot live without a good connection or a good uh computer or a good um you know sometimes our phones are attachment of ourselves already so these are you know the experience can be viewed in this life worlds according to van maanen okay so this is the example of the matrix that i did um in my research so i got off the statement what was said and then because this is hermeneutic phenomenology i was trying to say what are the things that the the participants are not saying but it's included in the context and i can

**[36:49]:** correlate it or triangulate it in the different parts of the data so after that what are the thematic categories if i cluster it what is it and then if i use the life worlds to analyze it where would this fit is this more on a live body or at this ratio relationality and all of that okay so these are examples and um towards the end i was able to look at what are the themes that relate to corporeality spatiality relationality and temporality so this is how i i describe the experience but after that because there's iterative process there's permanent circle i have to look at my um my fee my goal my goal is i wanted to describe and interpret the experience of non-chinese people being cared for by chinese nurses that's my aim now how do i describe it so all of the themes that i have uh identified i recalibrated it reorganize it

**[37:48]:** so that i can give more of a thorough description of the phenomenon so i looked at knowing persons through attention care and the themes are still there and some themes are there celebrating of expressions of caring and then trusting and finding hope and navigating the now and negotiating the next okay so this is my description of what the phenomenon is all about and then i even used um stories that would i i did a linguistic transformation of those themes and using you could use poems stories or different ways of expressing um your uh results so here i don't have to go through this but this is grounded approaches your glazer corbin and strauss charmaz they also have guidelines in doing this okay so you can see there are also re uh qualitative research that are not linked with any research tradition like it's not phenomenology it's not grounded here it's not ethnography it's just a

**[38:50]:** generic qualitative um description or qualitative uh analysis so most of the researchers use content analysis okay there are three approaches you have conventional direct content analysis or summative content analysis you could read your your pdf file for more discussions on this one okay usually the the framework um you have to be familiar with you with your data identify initial themes and then you start coding indexing clustering you chart them you map them and then you interpret so this is more of the general framework of how qualitative data analysis especially if you do not have any research tradition like phenomenology ethnography ground theory and so on and so forth you would also probably use focus group discussion fgd data you can do thematic analysis patterns you can look at where the points where they agree they disagree and all those group dynamics that are in in the fgd okay so you can look at the different

**[39:53]:** guidelines for critically appraising qualitative data analysis in transcription in the pdf file i don't have to go through that now uh before we leave okay i know this is just a one hour lecture but let me find out what uh what you think about this next question i need i need you to go up back to mentee mentee.com and sorry and let me just pull this up where is my mentee just a moment okay all right give me a second here

**[40:35]:** okay okay go to mentee.com and i want you to just just for fun okay um how confident are you in analyzing qualitative data this is a sliding scale okay so if you are confident in coding qualitative data how confident are you in using descriptive coding in vivo coding process and are you confident in using philosophical underpinnings so uh zero is strongly disagree if you're very confident then you use um strongly agree i think the number here is let me just see you have to encode the number six eight four two three nine nine all right i can see now good wonderful keep the data coming wonderful oh this is exciting real time data coming in all right people are more confident with uh descriptive coding wonderful maybe we need to have more um what i call it skill in using philosophical underpinnings in the research method that's okay that's wonderful all right it looks like

**[41:56]:** descriptive coding is a lot more you know easier probably great all right is there somebody who strongly agrees and very confident okay let me just take a screenshot of that

**[42:20]:** another screenshot okay all right all right wonderful i think you're able to to look at uh you know we cannot solve or we cannot improve our our uh skill in doing qualitative data analysis by just a lecture what you need to do is to do it okay so that you will be more familiar all right do you have any questions do you have questions put in the chat box if you have questions i know you wanted to eat your lunch now i'm i'm probably looking like your lunch already but if you have any questions please please write it in the chat box okay any questions or you can unmute yourself and um you can let me know if you have questions dr vilsenia do you have a question i can answer no ma'am very clear i would like to give you a clap oh wonderful thank you thank you dr belcinia okay so if you

**[43:34]:** have other questions you can ask dr bossinia or you can ask myself and we will try to answer it the best we could all right so thank you for uh joining us there are 87 people here it is at one point they were 90. i think this is um you know a good exercise i know for some people it's really hard to do the connectivity but um what do you think leave something on the chat box and tell me what you think about this lecture the synchronous lecture if you like it if you hated it or whatever it's okay i will not take it against you okay so leave something in the chat box if you you don't have anything thank you very much for listening and i hope that you will have a good lunch and that you can appreciate qualitative our research more thank you very much and have a good day thank you so much for your comments

**[44:31]:** i'm reading them i like it thank you very informative as asynchronous wonderful thank you mom thank you so thank you very much you can leave now and if you have questions put it in the chat box or you can email me if you have other concerns okay for the quiz for section c don't worry i will give you a notification i'll try to find solutions for that one thank you very much thank you for watching everyone thank you mom thank you thank you god bless great i will keep your chat so leave something on the chat box dr bersinia thank you so much section b thank you for joining us thank you record the first part it's horrible i i put myself recording zoom but i was too consumed with my presentation that i yeah maybe if you do this again you can ask me to co-host so that i will take charge oh i

**[45:26]:** should have done that it's so hard to be the lecturer at the same time you're you're doing the moderation yeah i can i can understand yeah thank you ma'am thank you bye bye take care how do i stop the recording