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Skewness measures (or refers to) a degree of asymmetry in the distribution of a variable.

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An oddly skewed distribution of p-values

I stumbled upon an odd result which I have difficulties to explain. In the following code, $x_1$ and $x_2$ are very similar variables. Yet the distribution of p-values for the coefficient in $x_1$ is ...
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21 views

How to deal with left skewed data and generalized linear models

I am trying to look at individual variation in Pielou's evenness of parasite communities. I have a study in which ~60 animals were sampled nine times (every two-three months for two years). Samples (...
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14 views

When is it better to exclude outliers and calculate the mean of the data instead of using the median?

I already searched on when to use the mean and median and I often see that median might be better than mean when the data is skewed, ordinal, include outliers, etc.. even tho, this might not be always ...
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10 views

Method for clustering multiple power law variables

Are there any clustering methods suitable for clustering high dimensional datasets that are composed of multiple highly skewed variables, including power law distributed variables? I am considering ...
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13 views

power analysis with different sample distributions

I need to perform a (two-sample) power analysis, however my data are differently distributed in both samples and I am not sure whether I can a standard approach through t-test. Please see the ...
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0answers
9 views

What would be a good sampler from pymc3 for highly skewed data

I have a gamma distributed data which is highly skewed - alpha=0.15, beta=0.001. I would like to perform mcmc to find the delta between two gamma distributions. I get the following error: I suspect ...
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1answer
34 views

Using bootstrap to estimate the 95th percentile and confidence interval for skewed data

The problem: I have data of sales per day during a certain period (n=7939). The data is rather skewed (see the first image below). I would like to propose the number of items to resupply every day ...
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1answer
57 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 ...
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17 views

When deciding a statistical test for certain distribution, should I consider all the observations, or the observations per condition one by one?

I wish my data was normally distributed. Is not. I have two conditions with 3 levels each. The data from one condition separated by levels, produces one very skewed distribution, and the other two ...
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1answer
49 views

Fréchet Hoeffding bounds for symmetric random variables

(Edited to clarify the question). The Hakan & Demirtas (2012 doi: 10.1198/tast.2011.10090) approach to approximating Pearson correlation bounds uses the concept of the Fréchet-Hoeffding bounds by ...
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1answer
32 views

Can I assess the relationship between a normally and non-normally distributed variable?

My study is related to the visual attractiveness of route-plans in a logistics context. In practice, route-plans are rejected based on the fact that they "do not look nice". I have conducted an ...
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1answer
31 views

Why don't I see my points on cullen and frey graph

I have a set of data of 5 members. based on some previous questions , I was expecting to see where my actual points are located on the graph. in my case I see the theoretical but not my points. just ...
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54 views

extreme right skewed data, bootstrap or mann-whitney?

I am an old dog (DB guy) trying to learn new tricks (stats) and was hoping someone here could tell me if this is a good approach: I have to analyse extremely right skewed counts of events over a ...
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2answers
454 views

Is a distribution still considered right-skewed if the majority of responses are zero?

i have a distribution in which the majority of cases take the value of zero and then there are a few (perhaps 10%) with values of 1,2 or 3. would this distribution still count as right skewed even ...
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1answer
37 views

What is a positively skewed distribution that can include zero?

I'm modelling data from a behavioural task. Participants do a few hundred trials. On each trial, they see a sequence of letters at a point on the screen and one of these letters appears surrounded by ...
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1answer
37 views

Why to remove skewness from the data?

I am a beginner in statistics and I read an article which said "Linear algorithms love normally distributed data". I wanted to know why do we have to transform the variable having skewness.
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43 views

How shape parameters are connected with mean, variance, skewness and kurtosis of generalized gamma distribution

I am writing a code in python that can generate probability distribution with given mean (m), variance (v), skewness (s) and kurtosis (k). In scipy library of python, there is a function named ...
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1answer
27 views

Frequency distribution curve - R language [duplicate]

We call a frequency distribution graph positively skewed if mode < median < mean. However for any graph if mode = median < mean, then what can we call it because the graph almost looks like ...
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28 views

How to model highly left skewed Ordinal Data

I have a data set of 16000 records of 5 ordinal variables(Customer Satisfaction(response variable), service, quality, knowledge, responsiveness) which are survey responses in 0-10 scale. All the ...
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1answer
20 views

Running MANOVA with Likert Scale Negative Skew

I am running a MANOVA in SPSS and I am finding that my Box’s test of equality of covariance matrices is significant. My sample size is 130 and I’m comparing 2 groups—one with 70 participants and one ...
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24 views

Skewed data: Is trimming the means necessary when using bootstrapping to compare means?

I want to compare four different groups on one dependent variable. Normally I'd do a one-way independent ANOVA, except that this time the normality assumption isn't met at all (see the below ...
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32 views

Testing mean assumption for mixture distribution

I have claim data structured by age groups and I am trying to test the assumed claim means for each age group against the actual data. It is a mixture distribution where around 75% of the sample ...
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16 views

Detecting anomalies in left skewed data

I have been given a problem at work which I'm unable to process. I have a set of data which is left skewed when plotting the normal distribution. Data below is captured on a monthly level, we only ...
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1answer
38 views

how to model this type of distribution?

I am trying to model this distribution in a generalized mixed model. the variable is a measure of number of number of years, reflecting start to end of reproduction, i.e. reproductive period. This ...
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51 views

Normalization of a positively skewed bimodal distribution

I have single cell RNA measurements (i.e. a big matrix where rows are genes measured in terms of counts of some reads that indicate the level of expression and the columns are the cells). The ...
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62 views

In a left skewed distribution, how can the range where 95% data lies?

In a simulation that I ran, I have the following graph as a result. How can I find the 95% confidence interval (i.e. the range where 95% of data lies for me). Since I am not expert in stats, please do ...
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1answer
142 views

Does 68–95–99.7 rule apply to skewed distributions as well and are they statistically correct?

I am not much familiar with statistics, but for my current simulation, I am using it to analyze my results from Monte-Carlo simulation. I understand the 68–95–99.7 rule. However, I want to confirm (...
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39 views

Estimating Kelley Skewness

Groeneveld et al have proposed the following measure of Skewness: $$\mathcal S(x, u) = \frac{F^{-1}(u; x) + F^{-1}(1 - u; x) - 2 F^{-1}(1/2; x)}{F^{-1}(u; x) - F^{-1}(1-u; x)}$$ where $F^{-1}(u; x)$ ...
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27 views

Transformations affecting skew and kurtosis

Given an arbitrary distribution, we can set the mean and standard deviation to any value we want by two invertible transformations, a subtraction and a division. If we first do the subtraction and set ...
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21 views

Permutation Test with 3rd and 4th Moments as test Statistic?

By permutation test, I mean the approximate Monte Carlo procedure often used, since it's often not feasible to compute all permutations of a pooled sample once the sample is large enough. Anyway, is ...
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13 views

Metric for calculating lopsided distributions

I have a list of ~20 numbers: 1200, 1200, 360, 360, 300, 250, 180, 180, 180, 180, 180, 90, 90, 90, 90, 45, 10, 0, 0 I am looking for a metric that determines the lopsidedness (maybe skewness) of ...
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10 views

Parametric correlation statistic for strongly-skewed data

The correlation depicted in the following plot (Pearsons's r=.28, p<.05) is the central result in one particular psychology study. I am wondering whether the skewness in the x-axis data would ...
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3answers
494 views

fitting a distribution to skewed data with negative values

I am trying to model data about altruistic behavior in a simple lab experiment. I have one value for each participant in the sample (N=479), describing how altruistic that person was. As you can see ...
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11 views

Simulating multivariate correlated data — with skew

I am trying to simulate datasets with > 10 variables where the correlations are known. However, some of the variables need to be skewed. I can use mvrnorm in the ...
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69 views

Correlation: how much skew is too much?

Most data for which Pearson correlations are calculated are not truly normal. I've seen textbooks cite +/- skewness of 2.0 as "too much skew" to rely on correlations as measures of association ...
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55 views

Bimodal distribution dispersion

what is the correct way to study the variability of a data set when all the observations are distributed like a bimodal distribution? For instance, here I identified the two modes as central index. ...
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1answer
287 views

Using r, how might I check whether a collection of data points are normally distributed with skew?

I currently have a vector containing values which I wish to consider the distribution of. I am aware that when using a qqnorm() plot, it is possible to see that data is normally distributed if it ...
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52 views

Advice on negatively skewed residuals

I am running a simple one-way ANOVA of a continuous dependent variable and my two-level categorical independent variable. n value = 408; 198 in my control condition and 210 in my experimental ...
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137 views

target variable is log skewed, and prediction is not good with high Mean Absolute Percent error

My dataset has a target variable e.g. production, which is very skewed. I can use log transformation to make it normal, e.g. log_production. when I use regression, or random forest model to make ...
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100 views

Standardizing with skewness and kurtosis

In statistics, standardization of data rescales data to have a mean of 0 and standard deviation of 1. Is there any sense in using skewness (the third moment) or kurtosis (the fourth moment) to ...
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1answer
240 views

What are the 'critical' values of skewness and kurtosis for normality assumption? [duplicate]

I am analyzing buy-and-hold abnormal returns of stocks (dependent variable) using OLS regression. These returns, however, tend to be positively skewed (and are so in my case). The residuals obtained ...
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97 views

KL divergence and anomaly detection

stats newbie here. I have a dataset that is collected weekly. In order to make sure the data set gathered this week conform to past observations, I'm using KL divergence to compute how similar the ...
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118 views

How to analyze right skewed data with a continuous DV?

I got my data from a questionnaire: group 1 had 30 individuals and group 2 also 30 individuals. They answered the same 6 questions where the opinions of others were exposed and after they could ...
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1answer
86 views

Learning model from skewed distribution

Say I have regression problem which is to predict score between [0,1] and data is really skewed. And train data set and test data set, # of regression answer label 0 is 10% and 1 is 90% (so I know ...
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82 views

Regression - extremely skewed response with a large, sparse matrix of boolean predictors

I'm working with a dataset that contains: $y$: the response variable that is 98% zero, but in the remaining 2% of cases it has extremely skewed real values (not integers), ranging from sub 1 to over ...
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37 views

Is it possible to test an interaction between an IV and (dichotomized) DV und the DV?

as my dependent variable (DV) showed a very high skewness (strongly positive) I was wondering of I might integrate the mean-or median splitted DV as additional independent variable in my model in ...
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89 views

Bootstrapping for the difference between two skewness and two kurtosis

I have two different time-series, T1 and T2, where skewness(T1)>skewness(T2)and kurtosis(T1)>kurtosis(T2). I want to test if these differences are statistically significant. I will use bootstrapping. ...
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122 views

Removing skewness does not improve the OLS model

I have built a Linear Regression model to predict class 8 enrolment using following predictor variables: No of classrooms, Female Population, Population of Age 13 children, the Literate population in ...
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93 views

Log alternatives for heavy right skewed dependent variable

I'm pretty new to training models and have previously used the log transform for right skewed dependent variables with good success. However, for my current mini-project's dataset it seems to be a ...