**584 normality-assumption questions.**

I have a paired data with n=66. I understand that normality condition of differences data should be met to conduct a paired t-test. However, from the histogram, it doesn't appear so normal. The p-...

I have one continuous variable (number of actions on a platform) and a ranked variable (education: values from 0 to 3). My research question is "Do people with more education perform more actions on ...

Simulations by Razali et al (2011) showed that the Shapiro-Wilk test of normality provided the most power (at a fixed significance level) when compared to Anderson-Darling, Kolmogorov-Smirnov, etc. My ...

In terms of testing the assumption of normality for a Point Biserial Correlation;
I have a dichotomous variable (1 = microsleep, 0 = no microsleep)
and a continuous variable (number of driving events ...

Must the input / independent variables in a generalized linear mixed model (GLMM) be normally distributed?

http://www.sthda.com/english/wiki/one-way-anova-test-in-r
Here it says when the LeveneTest has small p-value we can use the alternative one
...

I'm pretty new in statistical testing and I'd like some help in what I'm doing. I have two groups of scores from 0-100. Group A has 10 values and group B has 70 values. Initially I'm testing normality ...

I am confused about the normality assumption in repeated measures ANOVA. Specifically, I am wondering what kind of normality exactly should be satisfied. In reading the literature and the answers on ...

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 - \...

Does it make sense to conduct an instrumental variables model where the endogenous variable of interest is continuous but not normally distributed? I know for normal regression purposes, there is no ...

As a neuropsychology graduate student with some experience in statistics (I'm usually the guy other psychologists come to with statistics problems after trying it themselves but before seeing a ...

I have two questions related to time series forecasting with ARIMA:
Does ARIMA require normally distributed errors or normally distributed input data ?
Are there any assumptions on input time series ...

I apologize for this easy/basic question. Please forgive me if this is a duplicate question.
I've been researching the Shapiro-Wilk test (1965) of normality for a project. In doing so, I found an ...

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 ...

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 ...

I suppose I get frustrated every time I hear someone say that non-normality of residuals and /or heteroskedasticity violates OLS assumptions. To estimate parameters in an OLS model neither of these ...

I have what is probably a silly question regarding normality assumptions for t/Z tests. As I understand, t/z tests require that sample data was obtained from populations following a normal ...

If a probability distribution has, say, 112 bins with around 29000 samples, with the maximum probability of a bin being less than 0.05, is the Jarque-Bera test an effective measure of conformance to a ...

I am in the porcess of checking the assumptions of some data in order to perform a T-Test and had a few questions about how they should be set up. I was able to find the assumptions for a T-test here....

I have data on weight of a group of people after and before a diet. I want to see if weight loss is distributed normally.
...

I have a mathematical equation, based on physics, that requires estimating several parameters via nonlinear regression. I have conducted such nonlinear regression estimation with a dataset of 1100 ...

In testing for the normality assumption for 2 way ANOVA, the question whether normality within cells implies normality of residuals has been asked before and I have found so far different answers from ...

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 ...

I am trying to understand how Shapiro-Wilk test functions. So far, I have come across the following links:
How are the values in the Shapiro Wilk weight table calculated?
which explains how to ...

Why is the F-test for difference in variance so sensitive to the assumption of normal distribution, even for large $N$?
I have tried to search the web and visited the library, but none of it gave any ...

I'm an amateur statistician. I do it mostly for fun. I'm finishing up on my first semester stats class that covers up to hypothesis testing. I'm planning on beginning learning simple regression ...

I ran an between-subjects repeated measures (2*2*2) ANOVA in SPSS using GLM.
One of my dependent variables didn't meet the Test of Normality (Shapiro-Wilk p = 0.047) according to the table. The Q-Q ...

I try the shapiro.test for my transformed dataset (logarithm). I obtain p value 0,0001207. I try to draw the graph of distribution and obtain this graph (I attached).
For you, do I have a normal ...

When is testing for normality necessary for machine learning with Big Data? Please give examples or counter examples.

I get a little bit confused by the conclusions I can take or not with these small samples.
I have been measuring the degradation of a pollutant for 9 days. I measured the remaining concentration and ...

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 ...

Background
I have two conditions: A and B, with around 400 measurement points for each condition.
The most common result for both conditions is around '700', and neither one has a result below '600'....

I would like to conduct a paired sample t test and thus, I'm checking for the assumptions of normality. Upon conducting normality testing, each group scores were found to be normally distributed ...

I just would like to understand some information about the joint normality and the margins. I read that the normal joint distribution almost always implies that the univariate margins are all normal.
...

I am doing exercise on Kaggle House Prising and I cannot understand something.
I watch and read articles for Normality test and more specifically JB test but I cannot understand why according to my ...

Is it mandatory to check for Multicollinearity and Normality in the independent variables for all types of Machine Learning Algorithms ?

i have several log-transformed continuous variables in my model and want to estimate their impact on likelihood of sale. can i include (natural) log transformed variables in a probit model? if so how ...

I am running a kstest on MATLAB. When I take the data directly, i.e. kstest(data), the result says that my data is non normal. ...

I have an unbalanced design with two factors, gender and site. I'm trying to test for differences in a size variable. Levene's test reveals that the data has equal variances. However, log transformed ...

So I was transforming data for machine learning purposes and checking whether I should use the data or log-transform it. In addition to creating histograms I decided to test for normality using ...

I have done so many research and have read so many posts and manuscripts to find an answer to my question but I'm getting more and more confused. So I found it best to ask my question directly.
As we ...

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I have recorded the electrical response at a specific brain region by applying pulses to the region of interest. The electrical stimulation was applied in ...

So, there is the question: is there any statistical methods exist to apply normality test (hypotesis check) for grouped data?
For example, take a look at data frame:
...

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 ...

I'm in a field that is overly concerned with transforming non-normal variables in an attempt to make them normal. However, it's also generally recognized that the standard transformations (e.g. log, ...

I have a paired sample data with n=21. The two values V1 and V2 are from two different time points for the same group. I want to see if there is any improvement/reduction in values at time 2(V2). Of ...

I was reading this article, where the author says that
Maximum Likelihood (ML) estimates are asymptotically normal if
the log-likelihood is asymptotically quadratic.
I have heard or read other ...

I'm building an Error Correction Model using the Engle-Granger approach with the following interest rates data:
Observations: 230
Periodicity: Monthly
I have the following model:
$$\Delta R_t = \...

I think I understood that normality of residuals may not be a problem if the sample is large enough (cf, here).
My question is: Would my sample be large enough to be analysed using a probit and an ...

I have a dataset that contains a range of values. I have created a frequency distribution of the values, and have included the plot below. To my untrained eye, it appears that the frequency ...

- normal-distribution
- regression
- anova
- hypothesis-testing
- t-test
- residuals
- assumptions
- data-transformation
- r
- distributions
- heteroscedasticity
- qq-plot
- nonparametric
- spss
- self-study
- multiple-regression
- skewness
- goodness-of-fit
- statistical-significance
- kolmogorov-smirnov
- central-limit-theorem
- repeated-measures
- time-series
- wilcoxon-mann-whitney
- small-sample

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