Normality Testing for Residuals in ANOVA using SPSS
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- Опубликовано: 22 авг 2024
- This video demonstrates how to test the normality of residuals in ANOVA using SPSS. Interpretation of results, including the Kolmogorov-Smirnov, Shapiro-Wilk, histogram, skewness, kurtosis, and Q-Q plot are reviewed.
Hey man, I swear I have been looking for this information for so long from asking university ibms, website, friends, chat gpt you gave me the answer please keep doing this you saved me thank youu
Thank you for sharing this! I'm writing my dissertation and was getting stuck on this spot. Thank you for also explaining what things mean!
This video helped me further understand ANOVA and how the various assumptions can be configured using SPSS.
great video! very helpful! thank you Dr. Tood Grande. You are doing a great job!
Thank you for your valuable tutorials
This helped so much thank you!!!!
Thank you for sharing this! It was very helpful.
Thanks Todd, your videos have been a great help!
You're welcome - thanks for watching -
Dr. Todd thanks for the video. I have three questions:
1- do we test residuals normality distribution for confirmarory factor analysis using the same method you demonstrated here?
2- how to treat the results of self-report data?
3- when developing a psychological test do we need to test item biasness?
Understanding that unstandardized and standardized residuals produce similar results regarding normality, what is the difference between the two?
Standardizing basically just gives each result as a standard deviation from the mean instead of on the original scale, so won't affect the shape of the histogram. Standardization is useful when comparing measurements on different scales
very helpful thank you
Can you please interprate the reason why there is some gaps in histogram during normality plot??
Thank you sir for the explanation. I would like to enquire, when i did the levene's test the result is significant which means it is not normal distributed but when i used the standardized residual the result is not significant which mean it is normal distribution. Can I proceed with SPANOVA test?
Respected Professor, Can i do one way Anova on individual items measured on a 5 point scale, which constitute a formative construct (not reflective)?. Most of the reviews say that i cant do one way Anova on individual likert items as they are ordinal in nature. Please clarify & give appropriate reference for the same. Thanks
Great videos, as always! Thanks a lot!
You are quite welcome!
Good video
Is it possible to use multivariate instead of univariate to calculate many Residuals at once for different variables?
Thanks for your informative video, when you checked the normality for residuals the Factor list option is empty, i add two independent Variables in this option and it gives me different results. which one is true? putting independent variables in Factor list or this option should be empty?
Thanks
Thank you so much for the video! I just have another question about residual normality test in MANOVA. Is it the same procedure repeated multiple times for every dependent variable I have?
Thank you
Hi Todd! This video is awesome! Thank you very much!
I have a question related to handling non-normal data. I hope you can help me.
My N=15, I have 3 Conditions (X,Y,Z), and all the participants goes trough all 3 conditions. They are assigned to these Conditions randomly (eg. Participant 1 -> X,Z,Y; Participant 2 -> Y,X,Z etc).
Now my dependent variables are A, B, C. Theey are intervale scaled -> parametric.
So I want to check wheter the mean of A,B,C are different from each other.
My questions:
1. What test do I have to choose?
I think I have to choose ANOVA (repeated measure), because my N is dependent (my participants goes through all the conditions). So, I only have one group (experimental group).
2. In order to use ANOVA, the residuals of my DVs (A,B,C) have to be normaly distributed.
I checked that. But, now one of my Variable (A) is not normally distributed. The rest are normally distributed. But for my analysis I have to use all three Variables (A,B,C).
My question: Can I use ANOVA eventhough one of my Variable (A) is not normally distributed?
if no, what test can I use in this case?
3. Or should I transform variable A, so that it will be normal?
If yes, do I have to transform all my variables (A,B,C) in order to be able to compare each other?
I thank you very much for your reply! you would help me alot :-)
bests
I have one question: shouldn't you select the Factors under the Normality Tests window in order to test for normality of the dependent variable for EACH of the six groups separately?
Isn't the assumption normality of residuals in each group? That is, you have to check if the residuals are normal for each individual group. They could look normal on macrolevel, but with strong bimodality in each group.
So, its the same testing normality on each sample resulting from the combinations of factors and testing normality for all residuals together? plz i need a answer
I would like to know the same question.
dr todd please if i found the data is not normal distributed , what should i do ?
thank you! could you do similar for all the other assumptions of the linear model (homoscedascity etc etc)?
Why normality tests? Why dont we implement poissonity test? What makes normal distribution privileged among other distributions?
Thanks for this informative video! If you are looking at the normality of the raw data, you noted you need to look at it for each level/combination of variables that would be tested in the model. Do you not need to do this for the residuals? E.g., in your case, looking at the distribution of the residuals specifically in the subgroup of men in individual treatment, then in group treat, TaU, and the same for women?
Can you provide a citation for the use of residuals as the appropriate data to use in normality testing?
Hi Todd!
Thanks for your very informative and clear tutorials!
I am currently analysing the relationship between the 'number of pages in CSR reports' with various 'corporate characteristics' (Industry, Size of company, profitability)
As far as I understand, I need to do 'one way ANOVA' for each variable (corporate characteristic) and then produce box plots to show the results, followed by descriptive analysis. Does this sound like the correct method to analyse this type of data?
I have managed to produce the box plots, however, for the there are a few outliers.I am also wondering how to make it so that the box plot does not produce outliers as all the data is relevant and not a mistake. Am I right in saying this?
If you could help me, I will be eternally grateful!
Kindest Regards,
Matt
Thank you Todd you LADDDDD
Hi Todd, I do the same thing on the data but I do not get he residuals on my table as a variable. Do you know why that could be?
mee too :(
Haz el ANOVA sin pedirle pruebas de homogeneidad de varianzas (test de levene). No sé por qué razón cuando no activas ésta casilla te da los valore spredichos y residuales, una vez que los hayas obtenido vuelves a hacer la prueba activando la casilla para que te de éstos resultados:)
Why didn't he mention what to do if the residuals are not normally distributed? A big dislike.