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Questions tagged [skewness]

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

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Skewness Impact on Classification

I have a dataset with 134 attributes and my goal is to build a binary classification model. While exploring the dataset, I found that there was high skewness present in the attributes. I wanted to ...
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Central Tendency for Negatively Skewed Data

I am trying to understand how to best describe left or negatively skewed data in terms of central tendency. I have provided code below that simulates such a distribution, as well as the source code ...
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Distribution to use in a regression with a positive skewed variable with many zeros (homicide rates)

I want to study the determinants of homicide rates. However, I see when exploring the data that my dependent variable (homicide rates) has many zeros and is positive skewed. Which distribution family /...
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benchmarking a right skewed distribution

I'm benchmarking procedure groupings done in a hospital and all the items associated with the cost of the procedure. As you can imagine the range can be from .01 to 50k dollars per item. With the ...
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Variance of squared truncated normal

What is $$ \text{var}\left[v+\frac{1}{2} X \left(\frac{v-\mu}{\sigma}\right)^2 \mid v \leq \mu \right],$$ where $v$ is normally distributed $\mathcal{N}(\mu,\sigma)$ and $X>0$?
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Higher moments of linear regression residuals?

I previously asked this on Math StackExchange, with no success, but this post will add to that with some simulations. Background In the following linear regression with i.i.d $\epsilon_i$ $(i = 1, \...
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Violating the assumptions of one sample t-test and wilcoxon's sign test

As far as the background of my research is concerned, I developed a framework for sustainability management in organizations through a systematic review of literature and sustainability reports. That ...
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Is there a probability distribution with unskewed confidence intervals for quantile estimation?

The so-called process capability index Cpk is often used to express the yield Y in a production, e.g. for a given upper specification limit x. Mathematically it is based on fitting a normal ...
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How to compare rigth skewed data with non-parametric test?! Which test is the right one

Hi im trying to compare cells size from multiple locations. I have 5 biopsy locations from 25 individuals = 125 single tissue biopsies. The cell size is aquired using digital image processing and one ...
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1answer
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how to resolve skewness problem in regression

I'm working on a regression problem. The dependant variable is skewed and has a distribution as below I'm applying the log transformation but the resulting data is also skewed and is like below. ...
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Can two different distributions have the same value of mean, variance, skewness, and kurtosis?

Assuming that you have two discrete population distributions. Can they have identical values of mean ,variance, skewness and kurtosis while being different in shape visually ? Do these four values ...
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What is the relationship of skew and sample size on the sampling distribution?

I'm interested in the relationship between a distribution's skew and the sample size needed for the sampling distribution to be approximately normal. Let's assume the distribution is unimodal. In ...
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Skewness and Kurtosis estimation methods [closed]

In finance time series literature ARCH and GARCH models are used to get an estimate of volatility. Are there similar models to estimate skewness and kurtosis?
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Sufficient sample size for skewed populations

I have measured 50000 individuals from a certain population, and 800 (~1.6%) of them have a certain characteristic (say green eyes). I can be pretty sure that this is an effect that is present in a ...
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1answer
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How do you find shape parameters of a Johnson distribution from skew and kurtosis?

I'm trying to generate random numbers from a distribution with given moments, in my field the Johnson family of distributions is typically used but I can't find anywhere how to set it's shape ...
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Modelling my own cost function for skewed distributions

A while ago I worked in a model used for fraud detection, as that involved a very asymmetric distribution, I used F1-score as my loss function. However, I cannot stop thinking about it, and I feel F1-...
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Is there any non-gaussian distribution has skewness 0 and kurtosis 3?

Is there any non-gaussian distribution has skewness $0$ and kurtosis $3$? Thanks!
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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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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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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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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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1answer
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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
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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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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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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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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
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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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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
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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
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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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1answer
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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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3answers
69 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
136 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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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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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
220 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
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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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1answer
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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
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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
135 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
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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
201 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
148 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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195 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
38 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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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
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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 ...