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

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Pattern recognition through moments

Can the extent of mean reversion and trend in a given price dataset be explained by a combination higher moments (skewness/kurtosis) of returns? If yes, how do we combine these moments to come up with ...
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18 views

How to apply Box Cox to train and test data?

I am trying to standardize my data to performing prediction on it. Some of the features in my data are skewed and hence I am applying Box Cox transformation to reduce skewness. My data also ...
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Which cases will the Mardia Skewness test, while the kurtosis would give us good results? [closed]

I know that for some symetric, unimodal distributions the skewness test do fine. But sometimes, I get really poor results for such distributions. When applying the kurtosis test - I get fine results. ...
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1answer
21 views

Estimate parameters for skew normal distribution

I know there is already at least one question answer with this, but I think the solution does not apply in my case. I have a population for which I know the mean, variance and skewness. I saw how to ...
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1answer
46 views

Is this a skewed distirbution or bimodal?

It appears that this distribution may be right skewed and bimodal. Or is it just right skewed only?
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1answer
39 views

Data Transformation Needed for Logistic Regression?

I'm planning to do logistic regression with my dependent variable as either with injury or no injury with one of my independent variables as average computer use. I have attached a sample ...
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38 views

Are kurtosis and skewness meaningful for comparing distributions such as gamma distributions with very pronounced shape parameters?

Are kurtosis and skewness meaningful for comparing distributions such as gamma distributions with very pronounced shape parameters? For instance, take the red distribution in the first plot here: ...
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43 views

Is there a specific name for this heavily skewed distribution?

I have a column chart that looks like this: The chart is not well labeled because of data privacy and security issues. However, I can give you some information about the data behind this chart. Let'...
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1answer
40 views

How to make sense of non-linear data transformations? What conclusions drawn can you apply to original data?

In stats class, the professor talked about the interest of transforming skewed data sets to make them more "normal". From what I've understood so far, the idea is that the normal curve has nice ...
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15 views

Relation discovery between two time series data

I'm looking at analyzing the relation between temperature & sales/searhes of particular product at a daily grain The relationship is little complex, for example Sales go up for low temperature ...
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23 views

Do I Need to Normalize Data and Compensate for Apparent Overdispersion in Funnel Plots Generated from a 1.2 Million Record Dataset?

I have an anonymized dataset with 1.2 million dog and cat surgical sterilization records from 81 clinics. I would like to measure inter-clinic variation in mortality rate as part of a preliminary ...
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92 views

Skewness and two-tailed hypothesis tests

I have a particular question of which I am unsure of the answer: "Using illustrative examples, explain the role of skewness of a statistical distribution in a two-tailed hypothesis test." My initial ...
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1answer
48 views

How to deal with skewness in IV

I'm Building a logistic regression model and one of my independent variables is very skewed at zero. How do you suggest that i deal with this situation?
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1answer
42 views

centering skewed predictors

I would appreciate assistance with the following: I am running a gamma-GLM model. As part of it, there is a two-way interaction between a categorical (2 levels) and an interval/continuous predictor. ...
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Is it possible estimating Conditional Skewness with Quantile Regressions?

I am studying Quantile Regressions (Koenker, R. and Bassett, G. (1978)). But i cant find a work that uses Quantile Regressions to estimate Conditional Skewness. There is some work/article who did ...
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16 views

Reliability of measurement scale of non-normal variables

I have 18 variables (measured in a Likert-scale) which should according to previous studies measure the same thing, let's say intelligence. I want to calculate the reliability of the sum variable of ...
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1answer
43 views

Sampling distribution of unbiased estimator

Is the sampling distribution of an unbiased estimator symmetrically centered around the true value of the parameter? Why? Why not? Intuitively I think the question above is true (since I can use the ...
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1answer
87 views

Positive skewness: what to do when transformations don't help?

I would like to perform General Linear Model with one response variable and two predictor variables (1 numeric, 1 categorical). The response variable is positively skewed and transformations don't ...
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2answers
64 views

Equivalent of a flipped lognormal distribution

What distribution could represent a "flipped" (skewed left) lognormal distribution? For ex: what name would you do to the distribution in the figure below? I fitted the histogram with a Beta ...
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1answer
52 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
21 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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71 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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19 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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21 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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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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1answer
417 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
30 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 0,...
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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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1answer
77 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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59 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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39 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
51 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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519 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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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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25 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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1answer
126 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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30 views

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
67 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
54 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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24 views

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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68 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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25 views

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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12 views

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
58 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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26 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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18 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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42 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 ...