# Questions tagged [normality-assumption]

Many statistical methods assume data or a model's residuals are normally distributed. Use this tag for questions about the assumption & testing of normality, or about normality as a *property*. Use [normal-distribution] for questions about the normal distribution per se.

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### Is normality testing 'essentially useless'?

A former colleague once argued to me as follows: We usually apply normality tests to the results of processes that, under the null, generate random variables that are only asymptotically or ...
45k views

### What if residuals are normally distributed, but y is not?

I've got a weird question. Assume that you have a small sample where the dependent variable that you're going to analyze with a simple linear model is highly left skewed. Thus you assume that $u$ is ...
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### Box-Cox like transformation for independent variables?

Is there a Box-Cox like transformation for independent variables? That is, a transformation that optimizes the $x$ variable so that the y~f(x) will make a more ...
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### Pearson's or Spearman's correlation with non-normal data

I get this question frequently enough in my statistics consulting work, that I thought I'd post it here. I have an answer, which is posted below, but I was keen to hear what others have to say. ...
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### Regression when the OLS residuals are not normally distributed

There are several threads on this site discussing how to determine if the OLS residuals are asymptotically normally distributed. Another way to evaluate the normality of the residuals with R code is ...
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### ANOVA assumption normality/normal distribution of residuals

The Wikipedia page on ANOVA lists three assumptions, namely: Independence of cases – this is an assumption of the model that simplifies the statistical analysis. Normality – the distributions of the ...
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### Interpreting QQplot - Is there any rule of thumb to decide for non-normality?

I have read enough threads on QQplots here to understand that a QQplot can be more informative than other normality tests. However, I am inexperienced with interpreting QQplots. I googled a lot; I ...
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### What references should be cited to support using 30 as a large enough sample size?

I have read/heard many times that the sample size of at least 30 units is considered as "large sample" (normality assumptions of means usually approximately holds due to the CLT, ...). Therefore, in ...
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### Normality of dependent variable = normality of residuals?

This issue seems to rear its ugly head all the time, and I'm trying to decapitate it for my own understanding of statistics (and sanity!). The assumptions of general linear models (t-test, ANOVA, ...
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### How robust is the independent samples t-test when the distributions of the samples are non-normal?

I've read that the t-test is "reasonably robust" when the distributions of the samples depart from normality. Of course, it's the sampling distribution of the differences that are important. I have ...
137k views

### Can I trust ANOVA results for a non-normally distributed DV?

I have analyzed an experiment with a repeated measures ANOVA. The ANOVA is a 3x2x2x2x3 with 2 between-subject factors and 3 within (N = 189). Error rate is the dependent variable. The distribution of ...
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### Standard deviation of standard deviation

What is an estimator of standard deviation of standard deviation if normality of data can be assumed?
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### Example of distribution where large sample size is necessary for central limit theorem

Some books state a sample size of size 30 or higher is necessary for the central limit theorem to give a good approximation for $\bar{X}$. I know this isn't enough for all distributions. I wish ...
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### Is Shapiro–Wilk the best normality test? Why might it be better than other tests like Anderson-Darling?

I have read somewhere in the literature that the Shapiro–Wilk test is considered to be the best normality test because for a given significance level, $\alpha$, the probability of rejecting the null ...
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### Testing normality

I have a large dataset (500000 data, V1 column include all the data). x <- read.csv("mydata.csv", header=F) hist(x) Which gives: Looking at the data, I ...
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### Assumptions of linear models and what to do if the residuals are not normally distributed

I am a little bit confused on what the assumptions of linear regression are. So far I checked whether: all of the explanatory variables correlated linearly with the response variable. (This was the ...
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### Appropriate normality tests for small samples

So far, I've been using the Shapiro-Wilk statistic in order to test normality assumptions in small samples. Could you please recommend another technique?
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### QQ plot does not match histogram

I have a histogram, kernel density and a fitted normal distribution of financial log returns, which are transformed into losses (signs are changed), and a normal QQ plot of these data: The QQ plot ...
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### If my histogram shows a bell-shaped curve, can I say my data is normally distributed?

I created a histogram for Respondent Age and managed to get a very nice bell-shaped curve, from which I concluded that the distribution is normal. Then I ran the normality test in SPSS, with n = 169. ...
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### What is the expected distribution of residuals in a generalized linear model?

I am performing a generalized linear model, where I have to specify a family different from the normal one. What is the expected distribution of residuals? For example, should the residuals be ...
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### How to test for differences between two group means when the data is not normally distributed?

I'll eliminate all the biological details and experiments and quote just the problem at hand and what I have done statistically. I would like to know if its right, and if not, how to proceed. If the ...
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### How to transform data to normality?

We have financial some data (500-1000 samples), which is not normally distributed (well known fact from the literature). I have some ideas to do parametric transformations of this data (using some ...
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1 vote
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### What to do when Kolmogorov-Smirnov test is significant for residuals of parametric test but skewness and kurtosis look normal?

I have conducted a parametric test in a study, n=290. I want to assess whether the residuals of this test are normally distributed. The skewness and kurtosis of the residuals are -0.017 and -0.438 ...
66k views

### If the t-test and the ANOVA for two groups are equivalent, why aren't their assumptions equivalent?

I'm sure I've got this completely wrapped round my head, but I just can't figure it out. The t-test compares two normal distributions using the Z distribution. That's why there's an assumption of ...
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### transformation to normality of the dependent variable in multiple regression

Is it really important to normalize dependent variables in multiple regression or are there any exceptions? My model is providing better results with more significant hypothesis when the DVs are not ...
17k views

### What normality assumptions are required for an unpaired t-test? And when are they met?

If we wish to conduct a paired t-test, the requirement is (if I understand correctly) that the mean difference between the matched units of measurement will be distributed normally. In paired t-test, ...
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