Can I ask a question about normal distribution as part of the assumptions in ANOVA please? Are we looking at normal distribution for the whole set of data or for each independent variable group? Say we're doing a one way ANOVA without repeated measures and we have 3 groups (A, B, C) who had one dependent variable measure (weight). Should we run normality test for each of A, B, and C ? Thank you
Are the residual normality test and the data normality test one and the same, or are they separate? I'm still a bit confused. As far as I understand and have learned, the residual normality test checks the normality of the difference between the observed y and the predicted y from a model (usually used in regression tests), while the data normality test examines the normality of the original data (typically used in paired tests like t-tests and ANOVA).
Hi the concept of "degrees of freedom" as commonly discussed in statistics (e.g., in the context of a t-test or chi-squared test) isn't directly applicable to the Shapiro-Wilk test in the same way. The Shapiro-Wilk test doesn't yield a "degrees of freedom" value like some other statistical tests. Instead, the test involves computing the W statistic based on the observed data and expected values under a normal distribution. The critical value to which you compare the W statistic depends on the sample size, and tables or software often provide these critical values for various significance levels and sample sizes. Regards, Hannah
i have question. i have done 2 research hyphotheis and their normaality tests.For eg i have said ho the perceivness . bout social media follows normal and h1 follows not normal.My test shows both my objectives are not normally distributed .so how to interprete in disccussion chapter and conlunsion
wow mam well explaniation about normalilty test, but I have question that for analitical method we have a threshold of 0.05 i.e if results are less than 0.05 we can say that data is not normal and vice versa, but for graphical method what if the data is near to normal distribnution, that when we can cofidently say that our data is normal or not. just like a fix threshold value of p in analytical method.
00:02 The video explains testing for normality. 01:00 Normality tests check if data fits a normal distribution 01:56 P-value and normal distribution 02:50 Normality tests help to check distribution types 03:52 Large sample size can lead to rejecting the assumption of normal distribution based on small p-values. 04:53 Use QQ plot for better assessment of normality 05:49 Using data tab for testing normal distribution 06:52 Understanding the importance of normality test in data analysis Crafted by Merlin AI.
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unbelievable, what kind of presentation this is
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You're very welcome! Many thanks for your nice Feedback! Regards Hannah
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Glad it was helpful and many thanks for the Feedback! Regards Hannah
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Great explanation on Normal Distribution!
Good work, clear explanation
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Good job
Many Thanks : ) Regards, Hannah
Can I ask a question about normal distribution as part of the assumptions in ANOVA please? Are we looking at normal distribution for the whole set of data or for each independent variable group?
Say we're doing a one way ANOVA without repeated measures and we have 3 groups (A, B, C) who had one dependent variable measure (weight). Should we run normality test for each of A, B, and C ?
Thank you
Are the residual normality test and the data normality test one and the same, or are they separate? I'm still a bit confused. As far as I understand and have learned, the residual normality test checks the normality of the difference between the observed y and the predicted y from a model (usually used in regression tests), while the data normality test examines the normality of the original data (typically used in paired tests like t-tests and ANOVA).
Thanks, great job
You're welcome and thanks for the nice feedback! Regards, Hannah
Why don't we assume the data isn't normally distributed? Is it because its much more difficult to disprove?
I love you guys ❤
What to do when normality test is positive for one parameter and negative for other parameter .
Then you look at the graphical solution and decide with best conscience. It is best if you also mention it in your research!
@@datatab thank you
What is the degree of freedom in Shapiro-Wilk test ?
Hi the concept of "degrees of freedom" as commonly discussed in statistics (e.g., in the context of a t-test or chi-squared test) isn't directly applicable to the Shapiro-Wilk test in the same way. The Shapiro-Wilk test doesn't yield a "degrees of freedom" value like some other statistical tests.
Instead, the test involves computing the W statistic based on the observed data and expected values under a normal distribution. The critical value to which you compare the W statistic depends on the sample size, and tables or software often provide these critical values for various significance levels and sample sizes.
Regards,
Hannah
Instead of obtained score can normal distribution test be applied on likert response?
i have question. i have done 2 research hyphotheis and their normaality tests.For eg i have said ho the perceivness . bout social media follows normal and h1 follows not normal.My test shows both my objectives are not normally distributed .so how to interprete in disccussion chapter and conlunsion
wow mam well explaniation about normalilty test, but I have question that for analitical method we have a threshold of 0.05 i.e if results are less than 0.05 we can say that data is not normal and vice versa, but for graphical method what if the data is near to normal distribnution, that when we can cofidently say that our data is normal or not. just like a fix threshold value of p in analytical method.
💙
Thanks : )
What accent it is?
I just bought a license for datatab as a token of respect for your teaching skills. Dear Dr. Volk-Jesussek, you rock!
Wonderful! Many many thanks for your nice feedback!!!! Regards Hannah
Very nice explanation you have done with DATAtab. I need to know how it can be done in Excel sheet.
Thanks for your nice feedback! : )
What are the two visual methods that the presenter mentions?
00:02 The video explains testing for normality.
01:00 Normality tests check if data fits a normal distribution
01:56 P-value and normal distribution
02:50 Normality tests help to check distribution types
03:52 Large sample size can lead to rejecting the assumption of normal distribution based on small p-values.
04:53 Use QQ plot for better assessment of normality
05:49 Using data tab for testing normal distribution
06:52 Understanding the importance of normality test in data analysis
Crafted by Merlin AI.
15 minutes till my submission deadline and I found you. Thank you so much ✌
Herzlichen Dank
Gerne : ) LG Hannah
thank you so much
You're welcome!
We should do this for all kind of study like crosectional study?
🎉🎉🎉🎉wow
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For data that is collected in a Likert Scale, won't the data always violate the normality assumption? Because, the likert scale takes discrete values.