Linked Questions

1 vote
0 answers

Why according to distribution graph it's normally distributed, but Jarque-Bera test shows non-normally distributed? [duplicate]

I am working on Kaggle's house pricing exercise and I cannot understand something. I watch and read articles on normality tests, and more specifically JB test, but I cannot understand why according to ...
Georgi's user avatar
  • 11
374 votes
15 answers

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 ...
shabbychef's user avatar
  • 14.5k
138 votes
3 answers

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 ...
MarkDollar's user avatar
  • 5,805
20 votes
3 answers

What tests do I use to confirm that residuals are normally distributed?

I have some data which looks from plotting a graph of residuals vs time almost normal but I want to be sure. How can I test for normality of error residuals?
pb1's user avatar
  • 201
9 votes
2 answers

Non-normality in residuals

I refer to this post which seems to question the importance of the normal distribution of the residuals, arguing that this together with heteroskedasticity could potentially be avoided by using ...
Cesare Camestre's user avatar
5 votes
1 answer

Jarque-Bera normality test in R

Jarque-Bera normality test has significant p-values even when there is skewness and kurtosis. Does that mean test is infering data distribution is approximately normal?
sigirisetti's user avatar
1 vote
2 answers

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 ...
user25551's user avatar
1 vote
2 answers

How to compute Shapiro-Wilk test power?

I test normality of 12 residuals that are obtained from resid(lm(...)) command via shapiro.test. Thus I know variance, mean, ...
petrbel's user avatar
  • 461
6 votes
2 answers

Comparing noisy data sequences to estimate the likelihood of them being produced by different instances of an identical Markov process

(Prompted to some extent by the answers already given by Shane and Srikant, I've rewritten this to try to clarify what I'm getting at, if only to myself.) Suppose we have several similar systems, ...
walkytalky's user avatar
  • 1,897
4 votes
0 answers

Is the Anderson-Darling test or Shapiro-Wilk test more powerful? [closed]

In the testing of normality, how would the 2 compare? Is one significantly better than the other?
data_miner's user avatar
1 vote
1 answer

Granger causality test in VAR framework: small sample

I am using Granger Causality Test in VAR framework to test the causal relationship between renewable energy consumption, gross domestic product (GDP) and carbon dioxide emissions in one country using ...
daizy's user avatar
  • 11
2 votes
2 answers

Do these Q-Q graphs show that the data is approximately normally distributed?

The ends of these graphs confuse me. I know most of the values fall on or near the line. But I am unsure of whether the data is indeed approximately normal. These are the two graphs. Plot 1: Plot ...
Chris's user avatar
  • 21