Linked Questions

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4answers
2k views

How is Y Normally Distributed in Linear Regression [duplicate]

I understand that $y_{i}$s are normally distributed because we assume that the residual is normally distributed which seems a decent assumption. Question: Does that mean $Y$ is also normally ...
6
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1answer
5k views

Does linear regression assume all variables (predictors and response) to be multivariate normal? [duplicate]

I stumbled on this really nice blog. http://www.statisticssolutions.com/assumptions-of-linear-regression/ It has mentioned- "the linear regression analysis requires all variables to be multivariate ...
1
vote
1answer
554 views

Normality test and Outlier detection [duplicate]

In this question, I would like to ask two things: outlier detection normality test Details are as follows: I need to detect and remove outliers in my data. Before doing that, I want to test if my ...
1
vote
0answers
102 views

Non-normal observations in regression modelling [duplicate]

I read an article that says the dependent variables in a regression model must be normally distributed. The way i understand it, is that the observations for the regression model must then be normally ...
0
votes
1answer
41 views

What is exactly the non-normality requisite for nonparametric tests? [duplicate]

As the title says, what is exactly what is being tested before deciding to use a non-parametric alternative test (as Kruskal-Wallis for ANOVA, or Mann-Whitney's U for student's t)? Most sources are ...
0
votes
0answers
70 views

Non-normal data and non-parametric tests [duplicate]

I have two non-normal variables (one DV, one IV) and a few 7-point Likert scale IVs (normally distributed). The non-normal variables are centrality scores from network analysis - DV is from the ...
0
votes
1answer
23 views

panel data model [duplicate]

Good Morning, I have a doubt. I am doing a panel data model to calculate the benchmarking of some companies in the sector. is there any test that I can apply to know if I use fixed or random effects? ...
1
vote
0answers
16 views

Skewed response variable LM [duplicate]

I have a positive asymmetric response variable in a regression model. One of the assumptions about linear model is that the stochastic component of the model is normally distributed. If I have a ...
52
votes
3answers
218k views

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 ...
45
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3answers
4k views

Where does the misconception that Y must be normally distributed come from?

Seemingly reputable sources claim that the dependent variable must be normally distributed: Model assumptions: $Y$ is normally distributed, errors are normally distributed, $e_i \sim N(0,\sigma^2)...
22
votes
6answers
16k views

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?
27
votes
3answers
43k 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 - \...
27
votes
5answers
41k views

How does linear regression use the normal distribution?

In linear regression, each predicted value is assumed to have been picked from a normal distribution of possible values. See below. But why is each predicted value assumed to have come from a normal ...
20
votes
3answers
18k views

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?
14
votes
5answers
3k views

Why Normality assumption in linear regression

My question is very simple: why we choose normal as the distribution that error term follows in the assumption of linear regression? Why we don't choose others like uniform, t or whatever?

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