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SPSS (8): Normal Distribution Test in 3 Approaches

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  • Опубліковано 19 сер 2024
  • Normality Test in SPSS
    This video shows how to test normality assumption of data in SPSS using plot, descriptive and normality tests. In SPSS, the skewness and kurtosis statistic values should be less than ± 1.0 to be considered normal.
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КОМЕНТАРІ • 27

  • @wafulamaraka7334
    @wafulamaraka7334 6 місяців тому +1

    Very educative! Kindly provide the data for practice

  • @user-yy8kj2st8j
    @user-yy8kj2st8j 2 місяці тому

    Bro you saved me!! Thanks a lot! 💪

  • @birdtutty
    @birdtutty 3 роки тому +4

    Thanks a lot! Very clear explained.

  • @chacanuag
    @chacanuag 3 роки тому +2

    Thanks for the explanation! really helped me!!!!

  • @devakithankam3720
    @devakithankam3720 3 роки тому +1

    THANK YOU SO MUCH...GOOD EXPLANATION.

  • @saranyaelangovan7866
    @saranyaelangovan7866 3 роки тому +1

    Very informative

  • @SF-fj6rr
    @SF-fj6rr 3 роки тому +1

    THANK YOUUU

  • @Uncommonrealist
    @Uncommonrealist 2 роки тому

    Is there a way to get residuals from the linear mixed model??

  • @jasvirkaur6619
    @jasvirkaur6619 2 роки тому

    Hi
    My variables are assessed on Likert scales. I am applying stepwise multiple regression analysis. Is it crucial to satisfy the normality assumption?
    I applied one sample kolmogorov test and Asymp sig value came out to be zero, does it say that my data is not normal?

  • @musiqueami4469
    @musiqueami4469 2 роки тому

    so if Kolmogorov Smirnov or/and Shapiro Wilk indicate rejection of the null hypothesis, but Levene test does indicate 'equal variances assumed', how do i move further to my analysis? Parametric or no parametric test? this is my case. Thank you

    • @RESEARCHHUB
      @RESEARCHHUB  2 роки тому

      If you sample size is large enough, and histogram looks rather normal, then go for parametric. You can also report non-parametric test results as additional robustness check

  • @beautyisinmind2163
    @beautyisinmind2163 2 роки тому

    can we check normality for individual independent variables only? or normality should be checked between independent vs dependent?

    • @RESEARCHHUB
      @RESEARCHHUB  2 роки тому

      most important is to check normality of the dependent variable

  • @komalchaudhary16
    @komalchaudhary16 2 роки тому

    skewness and kurtosis value should be between which values 0-1?

    • @RESEARCHHUB
      @RESEARCHHUB  2 роки тому

      In SPSS, the skewness and kurtosis statistic values should be less than ± 1.0 to be considered normal. For skewness, if the value is greater than + 1.0, the distribution is right skewed. If the value is less than -1.0, the distribution is left skewed.

  • @pygmalion80
    @pygmalion80 2 роки тому

    Thanks for the clarification! What if Skewness and kurtosis are in an acceptable range but the Sig value is still 0.00? Can we still say the data is normally distributed?

    • @RESEARCHHUB
      @RESEARCHHUB  2 роки тому +1

      That is very unlikely

    • @pygmalion80
      @pygmalion80 2 роки тому

      @@RESEARCHHUB Even in 5-point Likert Scale questionnaires ?

  • @ravinathrathnayake2190
    @ravinathrathnayake2190 4 роки тому

    if kurtosis value is near .300, along with the skewness near 0, (in your case .196), can we conclude that the data is normally distributed?

  • @hiruniperera672
    @hiruniperera672 3 роки тому

    is read dependent variable?

    • @RESEARCHHUB
      @RESEARCHHUB  3 роки тому +1

      Here, we are doing it regardless of type of variable. See ua-cam.com/video/oivd9ekbAnA/v-deo.html

    • @RESEARCHHUB
      @RESEARCHHUB  3 роки тому

      Also, consider joining this free course researchhub.org/course/spss-for-beginners/

    • @hiruniperera672
      @hiruniperera672 3 роки тому

      @@RESEARCHHUB can i do the normality distribution test for the dependent variable using this?

    • @RESEARCHHUB
      @RESEARCHHUB  3 роки тому +1

      @@hiruniperera672 yes, of course.

  • @fathimathasleema1415
    @fathimathasleema1415 4 роки тому +1

    ,👍👍