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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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Should I normalise a sample drawn from a skewed population?

I am interested in the effect of the number of inhabitants of political entities on certain political behaviours within these entities. It happens that the number of inhabitants is not evenly ...
CNiessen's user avatar
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log transform left data in r

I am having trouble finding the transformation operation for left/negatively skewed data. The catch? All of my values are between 0 and 1. As such, trying the standard log10 transformation command ...
YouLocalRUser's user avatar
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Why does a small shape parameter in the skew normal distribution invert the skewness?

I am using the rsnorm function from the fGarch R library. As one would expect, for shape parameter (xi in this implementation) that is sufficiently large (abs(xi) > 1), a histogram has a clearly ...
Simon Mason's user avatar
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1 answer
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Vintage of this lower bound on skewness for positive data with given mean and sd?

It turns out there is a lower bound on the skewness $g_1$ of any strictly positive set of data having a given mean μ and standard deviation σ: $$ g_1 > \sigma/\mu - \mu/\sigma. $$ Although ...
David C. Norris's user avatar
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zero-inflation analysis multilevel for continuos data (not count data)

I was trying to fit a multilevel model, but I discovered that my dependent variable is highly skewed and zero-inflated. Individuals report 5 times a day for 7 days their level of paranoia and the ...
miso's user avatar
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8 votes
4 answers
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Estimate Box-Cox Transformation Lambda Using Skewness and Kurtosis

I would be interested in a method to find an appropriate Lambda parameter for the Box-Cox transformation based on only the skewness and the kurtosis of a given sample. I.e, if the skewness and ...
Hiro's user avatar
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How can a probability density distribution look negatively skewed on a graph but yield a positive skew result in Excel? [closed]

I am analyzing data from a young single mothers residential facility and I am seeing probability density plots that look clearly negatively skewed but Excel and calculates the dataset as being very ...
Rick Wobbe's user avatar
2 votes
1 answer
51 views

Why do the skewness and kurtosis formulae have powers of the variance in the denominator?

We calculate the variance as the centered 2nd moment $E[(X-\mu)^2]$. So when it comes to the skewness and kurtosis, why are the 3rd and 4th moments divided by the 3rd and 4th powers of $\sigma$? Why ...
ahron's user avatar
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Is a product that has 4.9 stars from ten customers better than one that has 4.5 stars from a hundred customers?

In many areas, we encounter a situation where we compare averages of highly skewed statistics using two unequally sized samples. Typically, this happens when comparing items in an online store. For ...
9 votes
3 answers
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When does positive skew imply median<mean?

For a random variable $X$, the skew is defined as $S(X):={\frac {E\overline{X}^3}{(E\overline{X}^2)^{3/2}}}$, where $\overline{X}=X-EX$. It is often claimed that positive (resp. negative) skew implies ...
2 votes
2 answers
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Logistic regression with highly left-skewed data for the independent variable

I am using the in-built GLM function in R to identify the model that best predict frogs' occupancy based on survey data. One of the independent variable (saturation) is highly skewed, as 36 of the 57 ...
Marco Lassandro's user avatar
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Inequality regarding measure of skewness & kurtosis [duplicate]

The measures of skewness and kurtosis respectively are $b_1=\frac{m_3^2}{m_2^3}$(skewness) and $b_2=\frac{m_4}{m_2^2}$(Kurtosis) where $m_r$ is the central moment of $rth$ order. That is $m_r = \frac{\...
Loves Mathematics's user avatar
2 votes
0 answers
44 views

One-way repeated measures ANOVA with skewed response

We have an experiment with 102 individuals in total. We have an outcome $Y$ (which is a variable related to the structure of a given bone), and we want to know whether this variable $Y$ differs ...
Leandro T.'s user avatar
2 votes
1 answer
108 views

How to normalise outputs of neural networks with different distribution?

I have a NN model that predicts 8 different variables. I use a multi-task learning approach, where I compute the loss between predictions and targets for each of ...
bird's user avatar
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3 votes
1 answer
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Zero variance but non-zero skewness

I was thinking of a hypothetical distribution where the mean(first cumulant) is non-zero, second cumulant(variance) is zero, and the third cumulant(skewness) is non-zero. The higher order cumulants ...
Abhinav Tahlani's user avatar
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Skew vs one sided standard deviation [closed]

If a unimodal dataset x with mean 0 E(x) = 0 is positively skewed E(x^3) > 0, does it imply that mean squared value of positive data (y: x/ x>0) is more than negative data (z: x/ x<0) ...
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Zero inflated and right skewed dependent variable – is the Tweedie distribution a good solution?

We are conducting a variance decomposition using a hierarchical linear random effects Bayesian model to investigate the variance in a DV that is affected by three nested layers. Because the DV is ...
james_westfield's user avatar
1 vote
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Creating and Using a Skewed Gaussian Distribution in Matlab [closed]

I am very new to matlab, and only used it to do some fairly basic math to visualize a method. Here is an example of what I've done with a normal distribution: ...
alwaystuck's user avatar
1 vote
1 answer
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Help finding unknown distribution (for fun)

I want to estimate the expected return of three different distributions. So there is this game I play, which has a function where you invest in a marketing campaign. There are three different types: ...
mafiaenshevnspiller's user avatar
6 votes
2 answers
636 views

Finding a distribution where skewness and kurtosis do not depend on each other. Does it even make sense?

I am simulating non-normal data to investigate how this affects some diagnostical methods that assume normality. In particular I'm interested in seeing how skewness and kurtosis affects the results. I'...
Vilman's user avatar
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4 votes
1 answer
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Which Levene statistic do I report?

I am writing a paper comparing quantitative values across $5$ groups. I have performed an ANOVA in SPSS 29 and have requested from the software the Levene statistic to judge if there is homogeneity in ...
user356816's user avatar
3 votes
2 answers
414 views

How to use one-sample t-test on skewed distributions?

I have been reading that people use the one-sample t-test also for skewed underlying distributions, saying that for a high enough number of datapoints (I read for example N=30 and N=100 in some places)...
Mars's user avatar
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Should I use a mean-based measure of skewness or a median-based measure of skewness, when the distribution has a very long tail?

I am aware that measures of skewness based on the mean are affected by outliers, and just one outlier can significantly shift the mean. However, in case of a distribution with a very long tail, should ...
Ommo's user avatar
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Reference about the Bowley’s coefficient of skewness

Introduction. In a test, I would like to use both the Fisher's moment coefficient of skewness (Joanes, 1998) $g_{\text{Fisher}} = \frac{m_3}{{m_2}^{3/2}} = \frac{\frac{1}{n}\sum_i (x_i - \overline{x})^...
Ommo's user avatar
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2 answers
132 views

How to decide better threshold values for variables with skewed distributions

In the context of optimizing loan advance decisions for customers with gold loan history, I aim to establish threshold values (x and y) to categorize customers into four groups based on loan count and ...
Thimali Fernando's user avatar
1 vote
1 answer
168 views

Tukey's IQR-method for outliers and highly skewed data

I am writing a thesis on performances on cognitive and linguistic measures. I have used the Tukey IQR method (Q1-1.5*IQR) to detect lower outliers in a non-normally distributed small sample of various ...
Samplename1's user avatar
1 vote
1 answer
46 views

Mean difference between four groups with

I have four categorical groups (A, B, C, D) each with one mean representing a numerical, skewed variable. The data structure is as follows: ...
Alaa's user avatar
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1 vote
0 answers
34 views

How to convert Standarized Mean Difference to OR in skewed data?

There are many methods to convert Standarized Mean Differences to Odds Ratios for meta-analysis (ln(OR) = -1.8 SMD), but none that i have found really deals with skewed summary data. Do you think i ...
san festein's user avatar
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1 answer
276 views

Which model for highly skewed data

The response variable in the dataset is highly skewed with a "ceiling effect". The errors of a fitted regression model, will thus also be skewed. I tried to fit a regression but as expected ...
Simone's user avatar
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Can you do a log transformation for excess kurtosis, or is that mainly used for skewness?

I am planning on doing a regression analysis on STATA on the financial performance of private equity funds. On my descriptive statistics, I saw higher levels of kurtosis and skewness. I decreased ...
Lucy's user avatar
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1 vote
2 answers
58 views

Should I transform my positively skewed predictor in hierarchical regression?

I'm doing a hierarchical regression trying to understand how intelligence (first predictor) and personality traits (second predictor) influence general knowledge (dependent variable). The problem is ...
sticker's user avatar
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0 answers
31 views

Is "skewing the data" and "skewing the results" just selection bias?

I recall various conversations with biologists, ecologists, and foresters that I neglected to ask for clarification on at the time. It doesn't occur in any of my statistics references. Sometimes in ...
Galen's user avatar
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1 answer
111 views

How to test overall skewness / normality in a large data set of ordinal data in R?

I want to test overall skewness / normality in a large data set of ordinal data from survey questions and was wondering how this can be done? (I couldn’t use Shapiro wilk as I received an error saying ...
izzi3880's user avatar
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0 answers
35 views

Centering a skewed predictor variable in a multilevel model that is involved in an 2-way interaction

Is there a correct method to center (mean or median centering) a skewed predictor variable in a multilevel model? The predictor is a skewed, count variable and will feature in a two-way interaction ...
ReadBeard's user avatar
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0 answers
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In a skewed sample with a large n, does Central Limit Theorem dictate that a t-test can be used, even if the mean cannot be interpreted? [duplicate]

I understand that, in the case of a highly skewed population and sample, the sampling distribution of the mean can still be normally distributed if the sample size is large, according to Central Limit ...
Josh Blake's user avatar
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38 views

Fixed Effects Regression, weird Residual Plots

I am running regressions analysing drought impacts on electricity generation based on fueltype of the generator. I transform the outcome variable (daily_generation) using an inverse hyperbolic sine ...
noricia's user avatar
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3 votes
1 answer
29 views

Increasing probability of middle-large values decreases skewness more than large values?

I found this counterintuitive result and want to check with you folks if I did not make any mistakes. Imagine a simple uniform distribution, of all values between 1 to 100. I would expect that ...
JMenezes's user avatar
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0 answers
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Differences in Pearson skewness coefficients [duplicate]

I downloaded this and that file. Then, I created histograms showing the daily cost and annual expenses per country. We observe that the histogram of cost21 is more symmetrical than the histogram of ...
Kώστας Κούδας's user avatar
2 votes
2 answers
49 views

Negative Coefficients for Interaction Term in Dichotomous Variables

I've come across an issue while analyzing some data and haven't been able to find a similar question on the site. I'm working with data concerning the impact of certain genes and smoking on the ...
Jorge A's user avatar
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4 votes
1 answer
442 views

How do I transform an extremely skewed distribution to use it for linear regression?

I'm currently working on a data set where the goal is to predict the number of rented bikes in Seoul, given information about the weather at the time. The data set can be downloaded here: https://...
Jan Philip Richter's user avatar
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0 answers
45 views

Influence of Large Data Size on Logistic Regression Fit and McFadden's $R^2$

I am currently working on a logistic regression analysis and have encountered a situation where I have approximately 16 million data points. I am interested in understanding the influence of such a ...
LeterPeko's user avatar
6 votes
2 answers
166 views

Can positive values with sd > mean have skewness = 0?

I'm trying to create an example of a distribution with all positive values, standard deviation > mean, and skewness =0 (third moment). I cannot. Is that possible? Can you prove it mathematically? ...
GabyLP's user avatar
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0 answers
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Comparing probability distributions from the same ML algorithm

Background: We are using a research tool that uses computer vision to quantify facial expressions (ie whether someone is smiling) from a webcam. The raw output for this tool is time series data ...
JWils's user avatar
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2 votes
1 answer
103 views

Log-likelihood skew-t

I am trying to write down the log-likelihood for the multivariate skewed student-t distribution, but I don't really get how to define it exactly. Could someone please tell me the definition as in how ...
BKS's user avatar
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0 votes
1 answer
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Can I do skewness on multiple standard deviation?

I have a 1000 sample of an electrical test at each 4 different time, so I do simple descriptive statistic to obtain standard deviation at each 4 different time. Can I then use skewness on standard ...
Ali Aizat's user avatar
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0 answers
50 views

Meaning of Skewness and Kurtosis values of Residual Errors in Time Series Forecasting Problem using LSTM

I have developed different kinds of RNNs (such as LSTM,GRU etc.)to predict future values of thermocouple measurements. The residual errors look like they do not follow normal distribution, so I wanted ...
MariaP's user avatar
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0 votes
0 answers
501 views

Cut off value of +/- 1.5 for Skewness and Kurtosis (Tabachnick & Fidell)

I've read multiple posts/papers citing Tabachnick and Fidell's cut off of +/- 1.5 as the acceptable range for skewness and kurtosis to determine normality; however, I cannot find it in their book. Can ...
Angel's user avatar
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2 votes
1 answer
94 views

Hazard ratio and skewness

Suppose the distribution $F$ is absolutely continuous. Is there a way to compare (i) the monotonocity of the hazard ratio (i.e., strictly decreasing/increasing); (ii) the skewness of the distribution (...
Seneca0681's user avatar
1 vote
0 answers
36 views

Power analysis to detect non-zero skew/kurtosis

Tests exist to determine whether a distribution is normal. For example the Shapiro-Wilk’s method. I'm wondering how to determine whether I'm powered to detect that my distribution is non-normal (e.g., ...
David B's user avatar
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2 votes
0 answers
104 views

What is the proper way to define skew distribution?

From What's the skewed-t distribution? there seems to be multiple way of defining skew distributions. However I am not sure if these methods are equivalent The original questions show methods from C. ...
Wakeme UpNow's user avatar

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