How to check normal distribution | The normality assumption

Подписаться 21 тыс.

Просмотров 1,1 тыс.

50% 1

See all my videos at:
www.tilestats....
1. Histogram
2. QQ plot (02:45)
3. Shapiro-Wilk (03:11)
4. An example of exponential distribution (08:40)
5. Type 1 and 2 errors in Shapiro-Wilk (10:49)
6. The normality assumption (14:49)
7. How to check the normality assumption (15:43)

Опубликовано:

11 сен 2024

Ссылка:

Скачать:

Готовим ссылку...

Добавить в:

Мой плейлист

Посмотреть позже

Комментарии : 8

@dawitabathun9402 2 месяца назад

great

@manuelleitner1996 8 месяцев назад

Thank you for your video. In the case of n>30 and highly skewed data, would you prefer a non-parametric test over the option of bootstrap? e.g. in a scenario where you analyze group differences, would you use a Mann-Whitney U Test or an unpaired t-test with 10k bootstrap samples?

@tilestats 8 месяцев назад

Hard to say because there are many types of skewed distributions. Anyway, in this video: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-mOzVwv9ob9Q.html I show that the MWU test has higher statistical power than the t-test for a log-normal distribution. I also tried permutation tests, such as the one shown in this video: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-v7u8lHgoWig.html and bootstrap confidence intervals (not shown in the video though) and they had a power between the MWU and the t-test. Thus for a log-normal distribution, MWU performs best. However, for other types of skewed distributions, you might get different results.

@manuelleitner1996 8 месяцев назад

@@tilestats thank you very much for your fast reply!

@tomkrechely4166 8 месяцев назад

Im waiting already to your next video. Btw, cant we use more robust tests when the data is highly skewed? And how much is highly skewed?

@tilestats 8 месяцев назад

Yes, you can use more robust tests for highly skewed data. However, to define highly skewed is somewhat arbitrary. In the video below, I show that a non-parametric test has a higher statistical power for highly skewed data compared to a parametric test: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-mOzVwv9ob9Q.html