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

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What can I say about this time series?

nobs 1256.000000; NAs 0.000000; Minimum -0.048947; Maximum 0.055384; 1. Quartile -0.004896; 3. Quartile 0.006744; Mean 0.000799; Median 0.000785; ...
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1answer
21 views

Gradient boosting regression trained on skewed data

My target feature is right-skewed. I want to apply gradient boosting regression algorithm to predict it but I'm not sure what kind of preprocessing should I apply. As gradient boosting is based on ...
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24 views

What are some good non-negative distributions for modeling data in Bayesian inference?

I'm just currently getting into the world of Bayesian machine learning, with a lot of frequentest stats background, and I frequently find myself limited in my modeling by my lack of knowledge about ...
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15 views

skewed data Distribution

I have a dataset with 97% of dependent variable of 0's, and 3 % of 1's. Want to apply machine learning models to predict output. What are the techniques of balancing or combating tactics before ML ...
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39 views

High proportion of zero values and PCA

My aim is to perform PCA since I have 76 variables in my dataset. Problem is that most of my variables are highly skewed as you can see in the histogram below. These variables are proportions ...
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39 views

Zero-inflated highly skewed predictor variables

I've thoroughly searched this website and multiple others and can't seem to find an answer to my question. This is also my first post so I hope I've followed all the rules. I apologise for the length, ...
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23 views

Distribution from mean, st. deviation and skewness [duplicate]

Is it possible to recreate distribution only from mean, standard deviation and skewness? I only have these parameters and no other information. Distribution represents the size of droplets. So far I'...
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1answer
31 views

Density chart of S&P500

I am examining the daily log returns of the S&P500 Index and I have negative skewness and excess kurtosis. However when I chart the density plot I am seeing positive skewness - does this seem ...
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1answer
39 views

In linear regression, data is highly skewed, transformation doesn't work..!

I have dataset with 9524 observations / 97 variables. Most of variables are numerical, and some of factor variables (Yes/no or several levels) I want to perform multiple linear regression with ...
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2answers
91 views

Application of Skewness and Kurtosis

Often in finance, stock prices are considered to follow a lognormal distribution while stock returns are considered to follow a normal distribution -prices are positive while returns can be negative(...
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1answer
56 views

Is there a skewed probability density function that models a normal distribution with two parameters, $σ_1$ and $σ_2$?

Is there a way to model data that are skew normally distributed, but for which one builds in two seperate standard deviations? The parameter $σ_1$ should specify the 15.9% to 50% interval, whereas $...
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21 views

What is the difference between skewed logistic regression and rare event logistic regression

I was doing a traffic safety analysis. My understanding is that if I have a sample that the response distribution differs a lot. for example, I have 200 events, but only 20 of them are crashes. I ...
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1answer
27 views

Are there theoretical reasons for choosing between similar distributions?

I'm interested in estimating the distributions of a few skewed datasets, for example extreme heat, and extreme rainfall. There are many distributions that can be fit to these kinds of data, for ...
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51 views

Comparing the means of two groups when a large number of data points have the same value

I have data on the profitability of wagers made according to two different strategies. One strategy was to bet $1 on the underdogs in each of a sequence of sporting matches. They have data like this: ...
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1answer
46 views

Fitting a left-skewed curve to data [closed]

I have the following data for x and y-axis inputs. I am trying to fit a left skewed curve (i.e. long right tail) with a steep right peak to this data in R. I am not sure what curve equation to use (...
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1answer
23 views

How to draw one standard deviation range around the mean of a skewed distribution [closed]

I have a distribution of data with a positive skew, shown in the image. The standard deviation is 1.34 and the mean is 2.01. I want to illustrate on the graph the range of values that are within one ...
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23 views

Correcting standard deviation with skew and kurtosis

Given a normally distributed set of values, it's possible to use 1 or 2 standard deviations to give a range where a randomly chosen data point is likely to fall, with some degree of certainty. If the ...
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1answer
86 views

Binary predictor with highly skewed distribution

I am running a linear regression model and I have a binary predictor that has a highly skewed distribution. For example, one category represents 96% of the data. In terms of frequency, the other 4% ...
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21 views

Remaining Skewness after log transformation

I am new in this community and I hope you could help me out. Right now I am working on a dataset which has multiple variables that are highly skewed. Below you can see one example of a variable ...
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3answers
67 views

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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1answer
70 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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0answers
17 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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11 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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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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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
75 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
73 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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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
68 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
34 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
50 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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2answers
86 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
467 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
68 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
59 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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126 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
33 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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35 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
23 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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36 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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36 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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21 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
40 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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67 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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156 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
262 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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43 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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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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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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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 ...