52. Factor Analysis in SPSS - II

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  • Опубликовано: 16 сен 2024
  • Correlation matrix, factor model, Bartlett Test of Sphericity, Principal component analysis, PCA and FA, Communality, Orthogonal

Комментарии • 7

  • @TheMathVirtuoso
    @TheMathVirtuoso 4 года назад

    Thank you very much, sir, for the detailed explanation. The concepts of the mathematics behind the EFA and CFA explained clearly in the series. The hands-on experience on the SPSS clears the procedure more perfect along with the meaning of the complicated tables in the output.

  • @sheetalgeriya1947
    @sheetalgeriya1947 3 года назад

    Thanks Sir. 😊

  • @ManjuSingh-jt9gu
    @ManjuSingh-jt9gu 4 года назад +1

    what if, their is only one component extracted?

  • @marvincommerce
    @marvincommerce 4 года назад

    thanks sir

  • @amishasingh7447
    @amishasingh7447 4 года назад +1

    Sir if the cumulative percentage is 54.55 and the KMO is 8.89
    Shall I continue with the factor analysis ?
    Also , if the rotated component matrix is showing only one component is extracted solution cant be rotated wht does this infer .?

  • @prasanthkumarp3962
    @prasanthkumarp3962 3 года назад

    Respected Sir,
    Greetings of the day!
    I have seen both the videos of factor analysis and trying to do the same with the dataset having variables Sir. While doing this
    1. While extracting factors based on Eigen value, I got only 1 factor with 80% of variance.then I have tried with fixed number of factors by giving input as 3, I got three factors.
    2. Everything went well till before step of rotation, there with Varimax rotation, my factors were loaded with multiple variables. So, I have tried Direct Oblimin method as my variables are related to farmer behaviour, then I got it...
    Sir, am I going in the right direction? If not kindly suggest the best way to do it.
    I am very much interested in learning factor analysis.
    Kindly help sir.

  • @mahipalmahato7648
    @mahipalmahato7648 Год назад

    5:41