Lecture 25- Factor Analysis

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[@jogendranayak420]

Thanks everyone. In case you need any more clarity on something related to this topic you may kindly post a question so that I can try to answer.

[@mbalinhleh356]

Jogendra Nayak objectives of factor analysis

[@chotabhim4814]

Sir I have done exploratory factor analysis with 540 sample size and 32 variables and find KMO, Anti image okay but 4 variables are less than 0.5 in communality and 10 factors derived in which 2 factors has 3 equal variables while 3 factors has 2 equal variables and rest 5 factors have 1-1 variable. What should I do to get 5or 6 factors in which most of the variables come.

[@lokeshpayasi]

wow sir. you have explained every thing. Can we also get PPT which you have shown there

[@BusinessCoachP]

No

[@tapaswinipanigrahi8948]

Thank you sir.

[@kossonouprunelle7576]

Sorry, I have both nominal and ordinal variable in my questionnaire, i took items from previous stuies and translate from english to french. Which one should i choose between EFA and CFA to check reliability and validity of my questionnaire? or should i use both of them? Thanks for your reply.

[@Asceticyogi]

Sir, Finally I came to understand the story behind, Thank you, sir, you have really explained in an easy way.

[@santoshyadavmathematicswor2056]

Nice explanation sir it's totally bhelp me to understand of data analysis in BRM

[@mr.sharma5317]

I am glad to see you again sir
Thank u sir

[@megalaughs89]

At the end I understand what this factor analysis about. Thank you Sir. Hope all the professors was as clear as you are.

[@2000PKMishra]

Sir u are from Odisha

[@khadarabdikhaire9854]

Thank you very much for your lecture

[@sharmasuraj858]

How to compute the "Factor Loadings"? Principal Components are the eigen values of the correlation matrix. Factor loadings are correlation of the variable with the factor. How to compute the value of this factor? Are the PCs the "factor" being talked about? I've checked this with SPSS. but the values did not came even closer to that. Please explain the steps after computing PCs as the eigen-vectors of the correlation matrix.
Thank you!

[@jayayanduri]

sir, you skipped the point about how to handle factor cross loading issues, can u please tell about that

[@ansumanabhisek]

Hello..sir..indeed it's a nice presentation..I wish to know sir..in case of questionnaire based survey, how to do pcm to reduce the no of questions questionnaire?

[@AmitKumar-pt7hb]

what i pcm..??? can u elaborate

[@amty1981]

Thank you sir for clarifying my concepts , it will help me in my research work @IITD.

[@artint25]

hi,
useful video,I am getting chi square value 1.00E4 ,in KMO and Bartlett test table can someone help me to figure out the error/problem

[@mbaprojectreports5867]

easy way to understand this video

[@I_LOVE_MATH_2000............]

a^4+b^4+20(Factor Analysis)

[@tubaathar2167]

really u explained very well sir....

[@gulerana8207]

Excellent 👍👍👍👍👍

[@abdulrasool1118]

weldone sir

[@sumitratnayake]

Excellent thanks 🙏

[@aarnavaaravdixit4947]

Excellent lecture sir.Its very very helpful, Waiting for more and more vedios of your.Thanks a lot sir.

[@xaviertoppo5964]

how much is the credit points of this subject?

[@sharmajidbeta]

Half

[@vidyashreejanamatti8192]

Awesome explanation sir nimdu👏

[@shudipchakma]

Thank you sir. it is very helpful for me. But one thing, do have any video of Cluster Analysis ? if not,
plz load one.

[@kirtijainani_managementlessons]

Thankyou sir informative video👌

[@kaustubhgupta9808]

Sir, you explained all these things to us in market research class in MBA. I was trying to remember exactly what you explained while applying it practically now while working in company. I was not able to remember completely but hopefully found your video here. Thanks for taking the effort to make this video.

[@muneebashraf5143]

❤

[@nallasurenderreddy6355]

Clear explanation
Thank you sir 🙏

[@MegaSil12]

very well exlplained sir,

[@AzzaUAE]

Well explained

[@suravisden]

Thanks Sir. this was really good.

[@dimplekaushik5554]

Thank you sir!!! today my all doubts are clear about favtor analysis....

[@swathics6936]

Thank you sir

[@namitasinha8310]

Thank you Sir

[@thisDash]

So basically the difference between FA and PCA is the variance used for the finding of the factors?

[@mangeshborse6284]

Very elaborative and well explained

[@biswojitbarik7433]

sir it's very simple understanding for us .i got a clear concet from it

[@aliijaz7250]

Excellent lecture indeed. Keep it up Prof

[@babushasiphone2020]

nice video #SEM

[@dr.khaleequzzamankhan593]

excellent lecture, thank you very much sir

[@jemgem9593]

Very helpful, thank you 🐚

[@siratfantu9386]

really useful lecture