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

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Linear mixed model with skewed residuals

I have a dataset of 720 observations, 15 each on 12 sites and in 4 points in time. My aim is to find out if there are differences in the measured variable between the sites and times of measurement. ...
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Statistical Analysis of a set of numbers [on hold]

so I have never taken a statistics class before, but have come across a problem which requires statistical analysis, so sorry if this is a very basic question. So I have a set of numbers: 1 , 3 , 4 ...
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36 views

Skewness for a sum of independent weighted bernoulli random variables with different probabilities of success

Suppose $Z_i$ are independent Bernoulli random variables with differing probabilities $P_i$. Also suppose weights $W_i$ are positive and constant. Let's define the random variable $S$ which is the ...
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1answer
11 views

Cost-sensitive SVM with sklearn

Is there a direct cost-sensitive implementation of the SVM classifiers (CS-SVM) within the sklearn module? There are several ad hoc methods for the cost-sensitive SVM on "the market", but I am ...
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68 views

How to overcome skewed component in validation of a 3 component likert scale

thanks for the information and input provided in the relevant posts. I intend to develop a psychometric questionnaire using Exploratory Factor Analysis; it gives 3 factors. One of the scales is ...
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12 views

Calculating SkewNormal Distribution with Std Dev & Skew Params

I'm trying to generate a skewnormal distribution from some parameters I will input manually, but I'm not confident in the scaling. I have this python code from another SO question (in python): ...
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10 views

Decision Tree with skewed input or missing data

Looking for guidance here. What say I have 100K training records and one of the categories/features has 99K same values and the other 1K of another value. E.g. 99K male and 1K female for gender, as ...
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36 views

predictor skewed but normality of errors

In linear regression (linearity assumption had been checked), what is the effect if distribution of predictor is skewed but errors are normally distributed? Is there a risk for estimation of ...
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382 views

What is skewness of a distribution?

What is skewness of a distribution? I ask it why any particular indices seem indecisive about symmetry, and in some case also about asymmetry.
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1answer
29 views

What is the best method to analyze these extremely skewed data with many zeros?

I'm working on my bachelor's thesis and have an analysis where the dependent variable (number of months of parental leave of fathers) has a very skewed distribution, as follows: 1089 times the value ...
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If you know the central moments of the data $X$, find a function $f$ for which $f(X)$ has arbitrary central moments

Say you are given one-dimensional data $X$, with mean $\mu$ and central moments $a_n$ which you know. Can you construct a function $f(x)$ which transforms the data such that $f(X)$ has the central ...
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Normalizing skewness with the Power or Box-Cox Transformation

Suppose I have a random sample drawn from an arbitrary strictly positive continuous distribution. Suppose moreover that I want to use the Box-Cox transform to zero out the skewness. Is there an ...
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68 views

Statistic on non-normalized data

Not that strong in statistics, so I need a little help getting started with some data I've gathered. In my experiment subjects had to perform tasks while I took time for them to complete it. Now, I ...
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53 views

Visualizing higher-order cross-moments (cokurtosis, coskewness)

How could and coskewness and cokurtosis be visualized in an easily comprehensible manner? Mean, variances, skewness, kurtosis can easily be illustrated in density plots: (Source: own *TeX-stuff) ...
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36 views

An asymmetrical distribution with mode at 0?

I am modelling some process where I logically want the residuals to have a maximum probability of being zero, but with more 'tolerance' towards positive residuals. So I'm looking for a distribution ...
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1answer
43 views

Is there skew/kurtosis on this plot?

I'm doing a stats assignment and for one of the questions I need to make a judgement of whether there is skew and kurtosis from a p-p plot in SPSS. I've been over the lecture, and we were told to look ...
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490 views

Why is left-skewed called negatively skewed and right-skewed called positively skewed?

I'm curious about the nomenclature: why is left-skewed called negatively skewed and right-skewed called positively skewed?
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18 views

Outliers detection or some roubust metrics on long tail sqewed distributions

I have a distribution of user sessions on the web site in the following format date,sessionId,price 2010-01-01,1,0 2010-01-01,2,0 2010-01-01,3,10 ... And I am ...
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19 views

What's the motivation of data transformation (like Box-Cox) to skew data?

What's the motivation of data transformation (like Box-Cox) to skew data? Suppose I am only interested in predictive power and non-linear model. Does it help to do data transformation (like Box-Cox) ...
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113 views

When does taking the log transformation of a univariate not remove skew?

So I was playing with some data today, and I plotted a histogram of it. I obtained the following distribution: Incredibly skewed! To fix this skewness, it makes sense to take the natural logarithm ...
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Model for highly skewed data

I have a highly skewed response variable with positive and negative values. It is a long-term data set. I already tried to transform the data using an exponential, alpha coefficient transformation ...
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1answer
59 views

What does positive skew show? [duplicate]

After collecting a sample my data is positively skewed, what does this show? I have collected data on the price of books and I have found my data to be positive skewed however I am not sure what this ...
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2answers
48 views

Data transformation for heavy tailed data for mixed model use

I am trying to transform my data to meet assumptions of a mixed model (lme4). This is the qqplot for the data. I have tried the traditional transformations: log & square root.
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log transform vs. resampling

I want to run a simple regression predicting score on some task, from number of minutes spent doing another activity. My N is ~800. The score variable is normally distributed and measured in ...
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63 views

Outlier removal in GLM

I was trying to solve the question below. I tried fitting a GLM (Gamma, with location and diseases as covariates) to fit the data, but the deviance was too large, possibly because of outliers. I Just ...
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Is it true that for $t\in[0,1/2]$ and $x\in[t,1-t]$ we have $f(x)\geq f(t)$ if $X$ is single peaked left-skewed with support $[0,1]$

From the typical plots of single peaked and left skewed distributions, I am guessing the statement is true. But is it possible to prove it formally or give a counter example?
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Testing for uniformity/skew of ordinal data

Setting: I have a large sample of posts made by politicians on social media. I know the topic of each of these posts (40 possible topics), and I know how popular each of the topics were compared to ...
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Factor Analysis for non-normal data

The data I received from a newly derived scale appears to be not normal. Can I still conduct a factor analysis on this data or would I have to do something else to reduce the dimensions? Thanks,
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24 views

Exclude outliers when most scores are 0

I'm doing a word learning experiment for which I prefer my participants to have no prior knowledge of the words. Prior knowledge is determined by a pre-test. Most participants indeed know 0 words ...
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1answer
43 views

Skewness of log-normal distribution only depending on variance?

Wikipedia says that the skewness of the log-normal distribution only depends on the variance of the underlying normal distribution. Skewness: However, from my point of view the skewness increases ...
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20 views

Hypothesis testing & inherently skewed data

I've run an experiment where I asked participants to indicate how they feel using a likert scale (1-7) in response to images they were being shown. The images were experimentally manipulated to ...
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15 views

Generating Skewed Z-Scores with Kurtosis

I am looking to programmatically generate random z-scores from a distribution with a specific skew and kurtosis. Can anyone provide a mathematical technique or code (VBA or C++ preferred but I'll take ...
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35 views

Is there a skewed distribution with zero tail index, mean zero and variance one?

I am looking for a skewed distribution with zero tail index (so no fat tails, ruling out the skew-t distribution for instance), mean zero and variance one. So far I have only found this on a skewed ...
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65 views

Statistical test to compare skewed distributions of binary data

I have two positively skewed distributions of binary data (0, 1) I would like to compare. I'm not an expert of non normal distributions. Is there a statistical (R based) test to do this? Thanks in ...
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How to analyze this positively skewed data?

I am having trouble analyzing my dataset consisting of the sumscores of a questionnaire. For each item, subjects had to indicate whether they performed this behavior 'never', 'sometimes', or 'often', ...
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How to add time estimates

Imagine I have a bunch at tasks to complete sequentially. There is some uncertainty about how long each task will take to complete. So for each task, we might estimate a 50% chance that it can be ...
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57 views

Quantify the asymmetry of a one dimensional vector

I have image data, which I can represent as one dimensional vectors. Each value represents the brightness of a pixel in a line. eg: (1, 12, 4, 3, 1, 4) I want ...
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analysing improvement in ordinal score in a group before and after an intervention

I am looking for direction in how to analyse ordinal data in a sample before and a sample after an intervention. I have performed an audit of safe drug syringe labelling practice in surgery before ...
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1answer
47 views

On skewed distributions, should the test/train/cross validation set be similar to the real set

On a skewed distribution (say there are two classes and the distribution is 2%-98%), given the small number of examples of one of the classes, would it be correct to have them distributed 50%-50% for ...
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1answer
31 views

Difficulty in calculating skewness

I'm trying to quantify the skewness of the distribution of random integer variable, generated in the interval from 1 to 15, with a function that I wrote in C++. Here are the generated values: ...
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239 views

Skewness Kurtosis Plot for different distribution

I am looking for a way to plot a skewness kurtosis plot of a range of distributions: Pearson systems, log normal, gamma , generalized gamma, Pareto 1,2,3,4 etc. I've only found some of these ...
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Multivariate asymmetric generalized gaussian distribution

I would like to write the distribution of a multivariate asymmetric generalized gaussian distribution and plot the result with Matlab. So far I was able to write the code to create a bivariate ...
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1answer
65 views

Right skewed asymmetric Gaussian-like distribution

I am trying to find a possible candidate as a fitting function for a distribution that looks like the following I know that this isn't a straightforward question, but I would like a simple function ...
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1answer
28 views

Skewed population example

"Consider a strongly skewed population (e.g., waiting times at airport security screening)." My book always uses that example when referring to skewed populations. I don't understand why would ...
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1answer
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testing dependent skewed samples

I must compare two distributions of patent data: namely, they are the number of patent applications of companies before vs after an acquisition. I need to perform an hypothesis test to assess if the ...
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2answers
100 views

Plot a highly skewed dataset

I have a dataset that contains music genres, songs and a "speechiness" rate. An example looks like this: ...
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96 views

Getting expected value from Standard Deviation and Skew?

If I have: - Standard deviation - Skew What additional information can I calculate ? Could I calculate Expected Value?
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1answer
293 views

Good Multivariate normality coefficient but suspicious univariate indices in AMOS, what to do?

We are conducting a research with 15 observed variables. Before starting a SEM model based on our data-set (of 531 cases), we tried to check for uni-variate & multivariate normality problems. The ...
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44 views

Normalizing logarithmic data in a range from 0 to 1

i am replicating a multilevel-analysis for my bachelor thesis (with newer data + corrections). The author i am citing used the unstandardized coefficients of every independent variable as beta ...
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24 views

Extended Standard Deviation - like functions, Skew, Kurtosis

I am gathering some performance data, and am doing the obvious storing the sum and sum of squares so I can calculate mean and deviation. And that would describe a normal distribution quite well. But ...