**598 assumptions questions.**

I've heard (sorry cannot provide a link to a text, something I have been told) that a high positive kurtosis of residuals can be problematic for accurate hypothesis tests and confidence intervals (and ...

I know the answer is likely to be 'it depends,' but I was just wondering..
in linear regression, which usually is considered worse in the following two cases and why?
case 1) presence of correlated ...

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 know this is a basic question, but I get slightly different answers everywhere I look, a quick example is that I learnt at Uni that the errors of the dependent variable have to be normally ...

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 ...

Does anyone know if are there some assumptions for Copula method? I heard from someone that the data should be i.i.d (independent and identically distributed). Let's say, if I want to capture the ...

I'm analyzing results from an experiment where 56 samples were tested for a specific response to electrical stimulation. Electrical stimulation was done at 2 different stimulation frequencies, and at ...

I would like to estimate a standard logit (panel data):
$\text{logit}(P(y_{i,t}=1))= \alpha + \beta_1 x^1_{i,t} + \beta_2 x^2_{i,t} +\epsilon_{i,t}$.
The problem I am facing, however, is that $x^2$ ...

In my lab, we are currently looking at how two handedness groups (mixed handed and consistent handed) differ in terms of lGI (local Gyrification Index, a cortical folding measure) across 74 different ...

I have been trying to find the major assumptions a Canonical Correspondence Analysis makes when doing its analysis. I have had a hard time finding anything useful. I did, however, find the assumptions ...

I am doing my thesis at the moment and I needed to check the BLUE assumptions for my data set. I am doing my thesis on trying to explain IPO underpricing and my data set consists of 100 companies who ...

I want to perform a MANOVA in SPSS as follows: i have a independent variable that consists of three groups (- of which the group sizes are not equal), and six dependent variables.
When checking the ...

I have a dataset where I calculated genetic distances between populations of some animals (a continuous variable). I want to know if these differences are explained by physical or/and ecological ...

In universitiy theses I often see students including details about their model in the appendix (distribution residuals, heteroscedasticity, durbin watson, multicolinearity values). However in ...

This isn't a strictly stats question--I can read all the textbooks about ANOVA assumptions--I'm trying to figure out how actual working analysts handle data that doesn't quite meet the assumptions. I'...

I am working on some simple linear modeling of a physical system and assumed that taking the derivative of an equation
$$Y = \beta_1 + \beta_2 X + \varepsilon$$
would give me
$$\frac{dY}{dt} = \...

I am dealing with a dependent variable that is either 0, 1 or 2 in theory it is unbounded and it can take values more than 2 so I am motivated to test Poisson model first.
The frequency counts for ...

I have a design where a number of object pairs were rated for association strength. These pairwise association ratings along 5 criteria of interest are expected to be used as IVs in a regression.
...

I ask this question out of curiosity
earlier today when i was trying to test for heteroscedasticity in R, i accidentally mistook ...

I understand the title is too generic. I tried to look for similar questions and although there were a few that were seemingly about the same issue, either they provided answers in the negative or had ...

This is in the context of two random variables. A frequent assumption (e.g. of the error term in ANOVA) is of independent and identically distributed random variables. There is a question on this site ...

I feel a little confused about the assumption of the ANOVA and what it ensures mathematically
the errors have to be iid and normally distributed N(0,1).
independance of observation. Is it not a ...

I have a question about a data analysis that I am running. I am analyzing the results of a survey in which (expectedly) there exists far fewer people in one group than in another. This survey is an ...

I'm stuck on some subtleties involved in simple linear regression formulation.
In a very general fashion I understood that the optimal point forecast for a random variable $Y$ (in terms of MSE ...

In linear regression, we make the following assumptions
The mean of the response,
$E(Y_i)$, at each set of values of the predictors, $(x_{1i}, x_{2i},…)$, is a Linear function of the predictors.
The ...

I am running analysis on clinical data collected from patients which are correlated either by time (longitudinally) or more commonly different measurements of the same person at same time (eg. ...

Imagine that you measure all $n$ people from a school class in $k$ $\geq2$ different treatment conditions. My goal is to find out whether the there is a systematic difference in Ranks (i.e. the $H_0$ ...

I was going through Poisson distribution and I understand the other assumptions made in Poisson distribution except for the last one which is:
The probability of an event in a small sub-interval is ...

Looking at this statement:
"Multicollinearity does not affect the predictive power but individual
predictor variable’s impact on the response variable could be
calculated wrongly."
Is this ...

Disguised as other questions, there are frequent questions where the OP checks for violations of model assumptions (e.g. normality, homogeneity of variance in linear regression) in models they intend ...

I did regression analysis.
It's about incoming calls and amount of orders.
I got a result like this.
summary(ireg)
Call:
lm(formula = 1/sqrt(ie) ~ ia + id)
Residuals:
...

Let $X_i:= (X_{i,1}, ..., X_{i,k}) $ for $i =1...n$ be $\mathbb{R}^k$-valued random Variables with $k\geq2$.
I wonder what the exact assumptions are to apply the Friedman test to Realisations of ...

BART builds on regression and classification tree models, and you can use it for continuous and binary outcomes (=probit). See Chipman 2010 for details.
With normal regression methods there are a ...

I have a data set where $100$ people made $500$ trips for $5$ days. I want to build a trip-level regression (zero-inflated Poisson) where the dependent variable will be the count of hard-braking in ...

Here are important assumptions that one has to check when performing a linear
Assumption 1: Homoscedasticity of residuals or equal variance (with Breusch-Pagan test for example)
Assumption 2: ...

I only have a very basic understanding of time series analysis. As I am learning ARIMA and then ARCH/GARCH models, I have some subtle (at least for me) questions on the common procedure to build such ...

Why does repeated measures ANOVA assume sphericity?
By sphericity I mean the assumption that the variance of all pairwise differences between groups should be the same.
In particular, I don't ...

Disclaimer: I don't have very much statistics experience.. I do have yearly climate data (yearly max temperature, total yearly precipitation...) for 200 years and want to perform the Mann-Kendall ...

If I estimate a Cox Proportional Hazards model and my covariate of interest is dependent (continuous or categorical), does the proportional hazards assumption still matter? I recently went to a ...

I just read Demand-Driven Forecasting: A Structured Approach to Forecasting(Wiley and SAS Business Series) and have a few doubts in Holt-Winters Model:
1) Unlike OLS Regression Modeling technique or ...

Some asked before "Why do random effect models require the effects to be uncorrelated with the input variables, while fixed effect models allow correlation?"
My question is: how do you check this ...

Assume that we want to compare the forecast quality of various forecasters $f$ on $n$ values such as stock-market prices or whatever. We could then define a "Mahalanobis-Distance" (MD) (or rather ...

I am learning survival analysis from this post on UCLA IDRE and got tripped up at section 1.2.1. The tutorial says:
... if the survival times were known to be exponentially distributed, then the ...

I'm trying to run a 2x3 mixed design ANOVA. Participants were measured on three different domains at two different times. One out of the 6 sets of results violates Levene's test while the rest do not. ...

I'm conducting multiple regression analyses using a sample of around 1200 participants. I'm first trying to identify relevant covariates to include in my model, in which I'm using ANOVA, t-tests, and ...

I'm looking for the correlation between a rank variable A and the proportion of blue (variable B) among 3 types of colour: blue, ...

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?

I am doing bayesian inference on normal data, and wonder how robust are the results with respects to some assumptions and potential mistakes.
Specifically, for simplicity I want to assume that ...

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 ...

I'm looking at a dataset of survival times of animals in two different groups. While there is some early mortality in the first group, the Kaplan-Meier survival curves overlap, the log-rank test and ...

- regression
- anova
- normality-assumption
- residuals
- heteroscedasticity
- multiple-regression
- r
- hypothesis-testing
- normal-distribution
- t-test
- logistic
- linear-model
- independence
- time-series
- generalized-linear-model
- least-squares
- ancova
- repeated-measures
- data-transformation
- cox-model
- mixed-model
- spss
- survival
- nonparametric
- multicollinearity

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