Jarque-Bera test explained: skewness, kurtosis, and normality (Excel)
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- Опубликовано: 28 апр 2021
- Jarque and Bera (1980) proposed a very simple and intuitive test for normality that utilises sample skewness and kurtosis and has become very prominent in quantitative research. Today we are discussing the concepts behind the Jarque-Bera test and learning how to apply it in Excel.
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Excellent explanation! Thanks a lot!
Your videos are absolutely amazing !!
Thank you so much, Im looking for those papers. You're amazing!!!
Thank you! This was very helpful. Your explanation is clear and easy to understand!
amazing explanation
Absolute legend!
Its really helping. Plz make vedio on how to clean raw data before applying any statistical test.
Good video
Hi, Thank you for this video. My question is regarding choosing between the Shapiro Wilk test and the JB test. I have 1700 observation and I was wondering which of them is much better. I have read in some sources that for doing JB test I should have at least 2000 observation.
Gr8 video..sir video on Martingale Difference hypothesis tests such as Generalized Spectral (GS), Dominguez-Lobato (DL) and the automatic portmanteau test ll of great help
Hi, i would like to ask if its okay for my data to not be normally distributed if i'm going to use simple linear regression to test my hypothesis (if variable A has an impact on variable B). thanks!
Thank you very much for your videos.
Hello an thank you,
Thank you so much for your videos sir, it has helped me a lot in my project. I have a question. Can we transform a non-normal data to normal data?
Can I use it in 60 samples? Thanks