Linked Questions

2
votes
2answers
2k views

Regression on a non-normal dependent variable? [duplicate]

Does it matter if a dependent variable has a normal distribution or not when it is used in a regression?
301
votes
16answers
102k views

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 ...
70
votes
12answers
5k views

What are some of the most common misconceptions about linear regression?

I'm curious, for those of you who have extensive experience collaborating with other researchers, what are some of the most common misconceptions about linear regression that you encounter? I think ...
32
votes
5answers
8k views

Why do political polls have such large sample sizes?

When I watch the news I've noticed that the Gallup polls for things like presidential elections have [I assume random] sample sizes of well over 1,000. From what I remember from college statistics ...
28
votes
6answers
5k views

In layman's terms what is the difference between a model and a distribution?

The answers (definitions) defined on Wikipedia are arguably a bit cryptic to those unfamiliar with higher mathematics/statistics. In mathematical terms, a statistical model is usually thought of as ...
20
votes
5answers
4k views

Assumptions of multiple regression: how is normality assumption different from constant variance assumption?

I read that these are the conditions for using the multiple regression model: the residuals of the model are nearly normal, the variability of the residuals is nearly constant the residuals are ...
27
votes
3answers
42k views

What should I check for normality: raw data or residuals?

I've learnt that I must test for normality not on the raw data but their residuals. Should I calculate residuals and then do the Shapiro–Wilk's W test? Are residuals calculated as: $X_i - \...
20
votes
2answers
15k views

Choosing between $z$-test and $t$-test

Background: I'm giving a presentation to colleagues at work on hypothesis testing, and understand most of it fine but there's one aspect that I'm tying myself up in knots trying to understand as well ...
17
votes
4answers
14k views

Confirming the distribution of residuals in linear regression

Suppose we ran a simple linear regression $y=\beta_0+\beta_1x+u$, saved the residuals $\hat{u_i}$ and draw a histogram of distribution of residuals. If we get something which looks like a familiar ...
15
votes
1answer
17k views

Why are rlm() regression coefficient estimates different than lm() in R?

I am using rlm in the R MASS package to regress a multivariate linear model. It works well for a number of samples but I am getting quasi-null coefficients for a particular model: ...
4
votes
4answers
9k views

Which test to choose when the results from t-test and Wilcoxon test are different?

I have a sample of 48. According to the central limit theorem, I may consider means of every continuous variable in my sample to have a normal distribution. However, one variable has a mean of 14 +/- ...
3
votes
2answers
13k views

Why do we have to assume normality for a one-sample t-test?

As a consequence of the central limit theorem the sampling distribution of the sample means will always be normal whatever is the distribution of the variable we measure. From our sample we can ...
6
votes
2answers
7k views

How does OLS regression relate to generalised linear modelling

Can anyone please shed some light on the relationship between OLS and generalised linear model? Has it to do with the distribution of the error terms, general linear model requires normality in the ...
8
votes
2answers
4k views

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 ...
4
votes
3answers
8k views

Normality assumption and sample size

I know this is a very debated topic, even on this site, but I still couldn't find an answer to my problem. Recently I am working with large samples (300, 400 and more). For now, I am trying to use ...

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