Likert Scale Data Analysis and Interpretation of Results

[@LearnEnglishWithOrchid]

This is the outstanding one that educated me to finish my analyzing data. Special thanks to the professor. 🎉❤

[@Dr.Okolie]

Thank you very much for finding the video helpful. Pls, like and share the video.

[@dailybasis3460]

@@Dr.Okolie Can I have your email, i need your help.

[@ShamsherSingh-np2xw]

Sir your lecture on analyzing Likert Scale data was truly outstanding and immensely beneficial. I had been searching for the right resource for quite some time, but today I came across your lecture, which provided me with a clear and comprehensive understanding of how to analyze my data. Thanks

[@Dr.Okolie]

Thank you very much. Happy you found the video helpful. Pls, share and like. Best wishes.

[@ShamsherSingh-np2xw]

Sure, sir. I'll share this video among my friends

[@josephkiplagat1825]

Watching from Nairobi Kenya. Very educative

[@Dr.Okolie]

Thank you for watching

[@stephenlugaimukamu9187]

Thank you, Sir. for the best explanation of the Likert scale analysis and interpretation

[@Dr.Okolie]

Glad it was helpful! Pls share and like.

[@Extentone]

so powerful. I salute you sir. You are a great lecturer.

[@Dr.Okolie]

Thank you. Glad you found the video helpful

[@yusufibrahim1005]

Thank this is very clear and helpful lecture for better understanding to analysis and interpret the Likert scale data

[@Dr.Okolie]

Thank you for finding the video helpful. Pls, share and like

[@peaceagba7207]

Thank you Dr. Ugo, this is actually a great relief.

[@Dr.Okolie]

Glad it was helpful! Thank you so much for watching. Please share to your friends who may also find the tutorial helpful

[@happygoluckyoflife]

THANK YOU SO MUCH FOR THIS VIDEO! I've been so lost as to how to process and run my analysis for my Likert scale questions for my undergraduate thesis (my survey has tons of them). Your video really makes it simple and easy to understand. Thank you!

[@Dr.Okolie]

Glad it helped! Thank you very much for finding the video helpful.

[@malayahellen]

I have learned a lot. Your clear explanation and illustration have helped the analysis stage of my research. Much gratitude to you sir.

[@Dr.Okolie]

Thank you very much.

[@emmanueldjeulong3047]

This is an outstanding lecture. Thank you so much Dr.

[@Dr.Okolie]

Thank you very much for finding this video interesting. Please, like and share

[@funnystar3225]

Bless you for being the only video I could understand without any issue. Your teaching is impeccable.

[@Dr.Okolie]

Glad it helped! Please, like and share the video

[@gopzzie]

This video was so helpful. I am grateful to you Dr. Okolie!

[@Dr.Okolie]

Thank you too. Please, like and share the video. Best wishes

[@ossaichekwube1103]

You are truly a teacher. Thank you Sir

[@Dr.Okolie]

Thank you so much

[@izzatirahman9148]

I certainly need this tutorial, THANK YOU SO MUCH DR!

[@Dr.Okolie]

Thank you very much for finding the video helpful. Best wishes.

[@mosesifeanyi5955]

very insightful, thank you so much , I can now conclude my research

[@Dr.Okolie]

Thank you very much

[@Saaaeeda]

thank you dr Okolie...I never saw this easy method of calculation before. I will try this method.

[@Dr.Okolie]

Thanks for finding the video helpful. Pls, share and like. Best wishes

[@chemistryforclassix7666]

It was really helpful for me as an aspiring data analyst. Thank you Professor for such a detailed description of Likert Scale data analysis. I am following you on LinkedIn

[@Dr.Okolie]

Thank you very much

[@lenzengineering3958]

This is good, comprehensive and straight to the point

[@Dr.Okolie]

Thank you so much

[@ronti2492]

Excellent video Dr Okolie! Many thanks from an Australian PhD candidate, based in Poland, based at KIng's College London....!

[@Dr.Okolie]

Thank you very much @ronti2492 for finding this tutorial interesting and helpful. You can share in your research network. Best wishes.

[@megaflowergirl99]

really simplified data analysis for me! Thank you!

[@Dr.Okolie]

Best wishes.

[@StephenKhisa-rl9ke]

thanks for a very interesting presentation. have learnt a lot from you.

[@Dr.Okolie]

Glad to hear that!

[@deictservices]

Dr God bless u, Ur teaching is quite simple as am new with spss I have a strong passion to know more

[@Dr.Okolie]

Thanks and welcome

[@emmanuellugina796]

You have made Likert analysis so easy Prof

[@Dr.Okolie]

Thank you very much

[@ccuellar5785]

Thank you so much for sharing these tutorials! They've saved me! I am not a quantitative person, but you've made this really understandable and doable.

[@Dr.Okolie]

Glad I could help!

[@teneishaellis5480]

Wow, thank you for this. It was very insightful and I am happy that I ran across how to display my analysis is a succinct and conscious way. Thank you!

[@Dr.Okolie]

Glad it was helpful!

[@lorinail]

This was so helpful! It was very understandable and described the best way to share and interpret the data for my survey.

[@Dr.Okolie]

Glad it was helpful!

[@sangapratap2760]

thank you very much, sir, This is very informative for the researcher

[@Dr.Okolie]

Thank you very much for watching the video tutorial. Pls, like and share. Best wishes

[@samgathenge8763]

thank you very much for taking your time to educate us. Blessings

[@Dr.Okolie]

So nice of you. Please, like and share

[@AmakiriKurah]

THIS QUITE EDUCATING. CLEAR AND PRECISE. WELL DONE SIR.

[@Dr.Okolie]

Thank you so much. Glad the video helps

[@adeyemijohnson2576]

Thank you for the videos, very informative and helpful

[@Dr.Okolie]

Glad you like them!

[@dakdingmayian1161]

your outstanding lecture will give us insight a lot

[@Dr.Okolie]

Thank you so much for watching. Glad it helps

[@curiousquest_365]

Literally no match, just wonderful and meaningful

[@Dr.Okolie]

Thank you very much for watching. Please, like and share the video

[@sanmiidowu]

Thank you Dr for this tutorial, it is so helpful and clear.

[@Dr.Okolie]

Thank you very much for watching the tutorial video and finding it helpful. Pls, share and like the video

[@eleanorngong8322]

This is outstanding Thank you sir just what I needed at the moment

[@Dr.Okolie]

Glad I could help

[@mbulanyinadaphine6772]

Thank you Dr. It has given me great insight on how to deal with my likert scale- research

[@Dr.Okolie]

Glad it was helpful!

[@ericmachisi3490]

This is a great presentation, Dr.! I gained a lot from it!

[@Dr.Okolie]

Glad it was helpful!

[@reeceoakes9486]

Thank you ever so much, this is extremely helpful and really assisted me in my appraoch. Really amazing and thank you once again

[@Dr.Okolie]

Thank you very much for watching the tutorial and finding the tutorial helpful. Pls, share and like.

[@belindaschutte7484]

Thank you so much for this video it was VERY helpful and assisted me to understand how to code my data and import it on SPPS to do descriptive statistics.

[@Dr.Okolie]

kzbin.info/www/bejne/oIjbZ4SrfpqsmbM This video will help

[@esabaimansi2897]

Thank you sir, this helped me with my interpretation.

[@Dr.Okolie]

Best wishes

[@mercykadenyi257]

This is phenomenal.Thank you very much

[@Dr.Okolie]

Glad it was helpful! Please, like and share

[@nouraldeenameen9920]

Thank you so much, I really appreciate your hard work for helping us 🎉

[@Dr.Okolie]

Thank you for watching the video.

[@lawrencekazibwe9751]

Thanks alot Dr, it has been very informative

[@Dr.Okolie]

Thank you for finding the video helpful. Pls, share and like. Best wishes.

[@pinkisharma5217]

This is so helpful for me as well as my group ❤❤❤

[@Dr.Okolie]

Glad it was helpful!

[@kassahunmulatu1457]

Thanks, Dr for your very interesting and helpful presentation!

[@Dr.Okolie]

Glad it was helpful!

[@sufrero3589]

Thank you Dr. Ugo, appreciated this simple tutorial and useful... Love from India.

[@Dr.Okolie]

@sufrero3589, thank you very much for finding the tutorial helpful. Pls, share and like the tutorial. Best wishes.

[@digantamudoi1785]

Thank you, Dr Ugochukwu Sir. Really it is an excellent video on Likert Scale. Actually, I am pursuing PhD programme. This video helps me a lot in my research work. Sir, expecting more videos in future. D K Mudoi, Assam, India.

[@Dr.Okolie]

Thank you very much @digantamudoi1785 (D K Mudoi, Assam) for finding the tutorial helpful. Please, share to others who may learn from the video, and please subscribe to my channel to get a notification when next i post a new video. Best wishes.

[@digantamudoi1785]

@@Dr.Okolie Obviously Sir

[@OpokaJames-f1b]

This is very elaborate and easy to understand. Thank you

[@Dr.Okolie]

Glad it was helpful!

[@Iamstephen_st]

This has helped me in my analysis.

[@Dr.Okolie]

Thank you very much. Pls like and share the video

[@angelaokojide3920]

So impactful. Thanks so much.

[@Dr.Okolie]

Thank you so much for watching

[@sibusiso.dntshangase5875]

Very interesting Sir

[@Dr.Okolie]

So nice of you. Please, share and like the video

[@Zainab-n4g]

Well presented, thank you

[@Dr.Okolie]

Glad it was helpful! Thank you very much for watching the video tutorial

[@abrammupuwi2141]

This quite helpful as you have managed to illustrate every step, it really helped me in my presentation of results.

[@Dr.Okolie]

Thank you for finding the video helpful. Pls, like and share

[@abumathebula2657]

Thank you very much for your time and patience to impart this knowledge to us Dr Ugochukwu. It has been a conundrum to me to understand and appreciate likert scale data, but in one lecture that you provided I feel much love for likert scale data and I cant wait to start working with it.

[@Dr.Okolie]

Glad it was helpful! Thank you so much

[@atomscientist7305]

Thank you, very amazing lecture

[@Dr.Okolie]

Glad you liked it!

[@martharobert7146]

Thank you so much Dr. may Almighty God bless you abundantly. I was in between on how to analyze data on my Thesis.

[@Dr.Okolie]

Thank you too for finding the video helpful. Best wishes

[@andiliaugustinus8409]

well explained. thank you so much Prof.

[@Dr.Okolie]

Thank you.

[@G.B.JFreeman]

Excellent tutorial.

[@Dr.Okolie]

Thank you

[@francelinoximenes3281]

Thanks sir. Excellent data analysis and interpretation of the 5-point Likert scale. It will be much better if you explain more deeply "what MEAN and Standard Deviation stand for; and how they are applied in research both academic and non-academic (project)? This is good for the learners to understand it well. Sir you also need to show on SPPS how to produce the data set into Ms Word

[@michaelchiwaula1148]

I want to understand how to interpret the mean and standard deviation of the likert scale. I have not heard in the video the role of the standard deviation

[@loc404]

@@michaelchiwaula1148they’re actually meaningless . What is the mean of agree & disagree?

[@laouelmoustapha1171]

thanks Dr, i'am grateful of your explanations

[@Dr.Okolie]

Thank you.

[@SsosoAD]

You're the best really, I watched many videos but your lecture was very helpful. Thank you!!

[@Dr.Okolie]

Glad it was helpful!

[@LishaMo-o9u]

Thank you so much Dr. You've helped me a ton!! Best of luck to you!

[@Dr.Okolie]

Thank you very much. Glad it helped.

[@annomjames5060]

By the way I enjoyed learning from your tutorials. Thank you so much for the video.

[@Dr.Okolie]

Happy to hear that!

[@rilwanuadamu5372]

Really appreciate it Dr

[@Dr.Okolie]

It's my pleasure

[@silasosundwa4638]

Great stuff

[@Dr.Okolie]

Thank you very much

[@solomonmathewos1419]

Amazing Approach.

[@Dr.Okolie]

Glad it was helpful!. You also find this helpful too kzbin.info/www/bejne/lXjFenWqnJqsfZI

[@mayajha5038]

Excellent ! Thanks

[@Dr.Okolie]

Thanks so much

[@alirasoli4328]

helped me in the scenario, I was tackling about. hope you will share the knowledge you gained with others

[@Dr.Okolie]

Thank you very much for finding the tutorial helpful.

[@ufuomaahwinahwi5287]

Thank you for sharing your knowledge

[@Dr.Okolie]

Thank you very dear Ufuoma for finding the tutorial helpful and interesting. Pls, you may share the tutorial to others who may learn from it, like and subscribe. Best wishes.

[@asemotaminister7246]

@Dr. Okolie, sir how can i calculate the mean and standard deviation manually in the above sample.

[@oluchiobi3076]

Wow, thank you Dr. I learnt so much

[@Dr.Okolie]

Thank you so much Oluchi. Happy you found the tutorial interesting. Please, share and let your students learn from the tutorial too.

[@AdelowoAbimbolaDavid]

Thank you so much for this content. Please do you have literature that back up your decision on the weighted average in this video? Kindly share if there is any..... thanks.

[@hibas8078]

Thank you, Dr Ugochukwu. This is really insightful and very helpful. I was looking for a way to measure the results. This is the only useful video a have come across on. ps. I was looking for 3 days. 😅

[@Dr.Okolie]

Glad it was helpful! Please share and like.

[@lalissa1744]

Impressive from Ethiopia 😮

[@Dr.Okolie]

Thank you for finding the tutorial interesting.

[@Emeka241]

Great work Thank you Dr. Ugochukwu

[@Dr.Okolie]

Thank you so much for finding this tutorial helpful and liking my effort. Best wishes

[@OnwePaulChikaodili-bi6pf]

Thanks so much sir! Plz sir could you make a class or video on how to analysis demographic characteristics of respondents and how to use charts in SPSS!

[@Dr.Okolie]

@@OnwePaulChikaodili-bi6pf Thank you so much dear Paul. Sure, I will make a video on that soon.

[@amvenom2004]

be blessed there🎉

[@Dr.Okolie]

Thank you

[@nafeesabbasi2959]

Dear sir I am confused about one thing. what is the meaning of High perceived or Low Perceived? What it indicates? please make me understand clearly. even my data shows Neutral high numbers then if High perceived comes then what is meaning of it?

[@emetuchehillary4735]

Very helpful. Thank you.

[@Dr.Okolie]

Thank you very much. Please, share and like the video

[@abumathebula2657]

Thank you once again, Dr. for the outstanding work and explanations on likert scale data analysis and spss. I would like to ask if there are other references to the method of weighted averages that you applied in this video lecture, that you can reffer one to.

[@mainguyenthingoc8399]

thank you so much, I am struggle with interpreting the results.

[@Dr.Okolie]

Thank you too

[@Olwam_Mnqwazi]

You make it look so easy! Thank you

[@Dr.Okolie]

Thank you for watching the video

[@RUBA_JAABI]

This tutorial is very much useful and I will advise that next time you try to ensure you give more details especially in the area of transitioning from the data into a full report...Once more thank your time

[@Dr.Okolie]

Thank you for finding the tutorial helpful. Sure, your suggestion is welcome. Best wishes

[@kidanemariambaraki2528]

Thank you Dr. for the reply. It is you understand my concern. Yes this is good for descriptive analysis what you displayed. My concern is I have Likert scale data collected from the sample. I want to infer the population using this data with a significance test. That is why I asked you. If you have any reference in regard to this or any support, please do Dr. . Thank you for everything.

[@Dr.Okolie]

I suggest you do an analysis that allow you to establish relationships. Check out my video on Grouping Likert Scale data into continuous variables, and also, see my videos on regression analysis. This may be what you want

[@kidanemariambaraki2528]

Thank you Dr. for the support. I will

[@tuladharmeekha9998]

Dr Okolie, thank you very much. I want to back up my choice of using 'weighted average' to make the decision, can you please suggest?

[@Dr.Okolie]

The video is also a reference source

[@mostafaalaywan3704]

thank you so much Dr Okolie for this great video. plz I have some questions : your decision to classify the item to low or high perception based on the mean scores of the item itself without taking in consideration the distribution of reponses on the 5-categories (SA,A,UN,D,SD). the third item classified "low perception" and you wrote in the conclusion that "majority of participants had low perception " whereas 68.2% of them answered (SA+A) and 23.8% answered D+SD. how can interpret this contradiction? . Thank you in advanced Dr Okolie

[@chiomadorisonwurah9579]

why do your mean differ given that the total respondents is 160 and the total items is 10

[@eto5609]

I just found the answer (64 * 5) + (61 * 4) + (13 * 3) + (6 * 2) + (16 * 1) = 320 + 244 + 39 + 12 + 16 = 631 Mean = 631 / 160 Mean = 3.944 It is good to explain every step especially because of people that does not want to over-rely on the software

[@Dr.Okolie]

Great!

[@okwukwumiracle9764]

Where have you been all life sir. Thank you for this

[@Dr.Okolie]

Thank you so much. Pls, like the video and share

[@nuryusrinafauzi3654]

Hi Dr, may I know the source that says the mean above the weighted average is high perception and the mean below the weighted avergae is low perception? thank you dr

[@Dr.Okolie]

Thank you for watching the tutorial. Please, note that because the descriptive statistics of Mean, Standard Deviation, Frequencies and Percentages is about learning people's views or perceptions about a certain situation. The analysis does not allow researchers to establish cause and effects. Thus, because the researcher focuses on understanding the participants' views on certain situations in my own study, I decided to use "Low and High Perceptions" to interpret their data analysis outputs and make meaning of results. If you had watch the video carefully, you'll understand why I said "Low and High Perceptions". You can use either the frequency, percentage, standard deviation or the Mean to interpret data analysis output. In my demonstration in the video, I have used the Mean (Weighted Average or Mean) to interpret data outputs and make my own meaning of respondents' perceptions of the subject under study. This does not mean that when the value of weighted average is high, the researcher should call it "higher and low perceptions". Use the weighted average to interpret your data in your own study context. As for source, the video tutorial is already one. Hope these help.

[@Luckisto]

Hi Dr Okolie. I hope you will get time to respond to my question/s. Firstly, I am wondering if the analysis presented is credible, pardon my wording of the language, but I barely found your authored papers utilising this method from your Google Scholar handle. 1. Since the means include the values of those "undecided" responses, thus, the contribution of this category to the average is that their value is greater than "SD". Remember the scale 1, 2, 3, 4, 5. Should the "undecided" category be excluded? What is your comment on the impact of the "undecided" responses to the mean? 2. Considering point 1 above ("undecided" responses), I find it difficult to rely on the "weighted mean". Furthermore, I would appreciate finding sources that advance the above way of analysis, please share if you have any. 3. Please note that it is my first time coming across something like this and I am asking the above questions to learn this new way not to criticise you for no reason hence I even went through your Google Scholar profile.

[@Dr.Okolie]

Thanks for watching the tutorial video. First, I wonder if you should first become bias over an idea you are new to before seeking clarifications. Your comment; "I am wondering if the analysis presented is credible", is harsh. In one of my other videos, you also flagged the video for this same issue. Second, assigning 3 points to "undecided" or "neither agree nor disagree" or "neutral" has been used by seasoned researchers to ensure unambiguous responses to item statements in a survey. When "neutral" or "undecided" is marked as 3, it serves as a middle part between the 5s and 4s (Strongly agree and Agree) responses, and help to drag down the average. This is the same for responses heavy with 1s and 2s (Strongly disagree and Disagree). When "undecided" or "neutral" occupies 3 spot on a 5-point scale, it helps to reduce skewness of participants' responses toward positive (level of agreement) and negative (level of disagreement). Thus, it serves as a mid-point. I found it extremely useful and have used it in all my research works published in the best globally recognized academic Journals. Please, visit www.ucokolie.com.ng to read many of my top journal publications. When you design a survey with a mid-point "undecided" or "neutral", it means that you have taken into an account that some of your respondents may not want to respond to certain statements that concern them. For example, undecided could mean: "I don't want to talk", "I am neutral about this statement", "I don't care", etc., which is also a for of response, and helps to control the respondents' feelings. When you do not include a neutral point in your scale, you're indirectly forcing some of your respondents to respond to some item statements against their wishes. My responses above have indirectly addressed your worry about the value of 3 assigned to "undecided" being bigger than the values of 2 and 1 assigned to Strongly Disagree or Disagree (negative responses). Third. Because, you have not seen any of my papers published using descriptive statistics doesn't mean that I did not assign 3 points to the 5-point scales used for data collection in those studies. Descriptive statistics of frequencies, Means and percentages cannot be used to establish cause and effect (causality), thus, I group the responses into continuous variables to test hypotheses. I hope this addresses your worry about why I have not published a study using descriptive statistics. Finally. In my video, I explained carefully why I had used the weighted average value as against any other decision rules such as the Mean cut-off of 2.50 which is widely used by researchers in Nigeria. That you're new to the use of a weighted average doesn't mean you should question the credibility of a tutorial first before asking questions to such a new idea to you. I encourage you to watch that video again to understand my reasons for using the weighted average. Thank you, and best wishes

[@Luckisto]

@@Dr.Okolie Thank you for your detailed response. The comments you read from the other videos were made after this one only that you responded to the other comments first. I clearly understand your point of view and your "Nigerian" descriptive analysis as you put it. Your papers are great hence the reason why I was surprised on presenting something not depicted by any of your studies. As researchers, we should be open to criticism. Adopting a method that is questionable should awaken your traditional ways of doing things despite being widely adopted in Nigerian society as readers of your work are beyond that. Respondents can skip any question if they feel so hence none would be forced to respond if one excludes that. I am not suggesting you change your way of doing things, but just sharing my views. Once again thank you for explaining your view which confirms my initial doubt on the whole analysis. Let criticism not discourage you from creating content. For your knowledge, I admire the ways you clearly explain concepts hence I subscribed to your channel. However, asking questions or criticising should be viewed as positive to your channel as a form of engagement. I am looking forward to more content. Thus, continue shining.

[@SylvesterSitsope]

What scale or score make the test items not reliable? 0.3 or 0.5?

[@KseniaFreis]

Thank you so much for the tutorial!

[@Dr.Okolie]

Thank you too for watching the video

[@ericabakah5006]

well done boss

[@Dr.Okolie]

Thanks so much

[@SerishaSher]

Hi Dr... Can you please show us how to perform correlation calculation between 2 sets of ordinal data. For instance I wish to see if scores for items in perception correlated with scores in items for knowledge.

[@oseniridwan4934]

Can we follow this format to calculate manually ( by hand) ?

[@jonathanmubiru1473]

Thank you Dr Ugochukwu for the insightful video. Kindly advise, is there a way to efficiently transfer statistical information such as frequencies, percentages, mean, and standard deviation into a single table in Microsoft Word (Like the one you have used in this video). Is there a method or tool that can help streamline this process and allow you to input all this data into a table format at once?

[@Dr.Okolie]

Thank you for watching the video, and finding it helpful. There is no easy way to do that for now. You have to input the results manually in a table when writing out the results in Microsoft Word just like I did in the video.

[@jonathanmubiru1473]

Thank you so much for you guidance. I personally, truly appreciate your lessons @@Dr.Okolie

[@oluwanifemitemenu3309]

For the low perception and high perception thing, is there like a pattern to it? For example, in a particular item, more people choose Strongly agreed so the decision be high perceptive

[@Dr.Okolie]

If more people choose strongly agree, it describes how much they perceived or viewed the statement you presented to them (in this case, strongly). You cannot use descriptive statistics to make decisions. It is only used for describing situations or how your respondents view certain issues. If you want to establish cause and effect, you conduct inferential statistics like regression, ANOVA, etc.

[@akingbadewaliu1404]

This is interesting.

[@Dr.Okolie]

Glad you found it helpful

[@ettaaki8606]

What about qualifying the low and high into further categories like very low, low, high, very high. How can we do that?

[@folahassan5827]

Thanks for this video!!!

[@Dr.Okolie]

Thank you for watching the video

[@mets22]

Thanks for the presentation. Please it is a good practice to repeat the percentages during the interpretation of the results?.

[@Dr.Okolie]

You can always fine a more refined way to present your results