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

learn more… | top users | synonyms (2)

8
votes
1answer
94 views

Proof / derivation of skewness and kurtosis formulas

Can anyone explain to me where the formula of skewness or kurtosis comes from? (I mean its derivation.) What's the logic behind it? Who proved it?
0
votes
0answers
27 views

Is this poor transformation advice for predictive modeling?

I have gotten some advice from a PhD statistician on doing predictive modeling on large datasets (lots of variables AND lots of observations) that I should perform transformations to eliminate ...
0
votes
0answers
10 views

Non-normal data (ceiling effect) and intraclass correlation

I am wondering if there is any way of doing an intraclass correlation, two-way, mixed, with non-normal data (in this case a ceiling effect)? Alternatively, what the interpretation (if any) would be? ...
0
votes
0answers
21 views

Skewed variable - better log10 or ln? [duplicate]

I am building a logistic regression model and one of my independent variable sis heavily skewed. Is it better to use the ln or the log10? Why? And how to correct the skewness of a variable that ...
3
votes
1answer
26 views

Compare skewness of many distributions with few observations

I have a dataset with page view data for about 500,000 users, divided into two groups. Each user can visit up to 5 pages, each as many or as few times as they want. So for each user, I have the ...
0
votes
0answers
14 views

How to improve results when using sampling in skewed binary classification?

I am using a data set with 18 features with True/False output (Related to mobile ad targeting). True values occurs only 0.4 % of the time. So, I have used sampling to keep the ratio of True and False ...
0
votes
1answer
29 views

How to deal with a skewed class in binary classification having many features?

I am doing data analysis in the mobile ad targeting domain. I have around 18 features and for a combination of these features, the result is either True or False (1/0) depending on whether the ...
4
votes
3answers
82 views

What is the reason the $\log$ transformation is used with right-skewed distributions?

I once heard that log transformation is the most popular one for right-skewed distributions in linear regression or quantile regression I would like to know is there any reason underlying this ...
0
votes
0answers
20 views

Computing the Correlation with Skewed Repeated Measures Data

Suppose I have two variables (e.g., Blood Pressure and Cholesterol) and I want to investigate their association across time. Also suppose that each individual has been measured three times ...
2
votes
0answers
49 views

Is it possible to build a curve with a given skewness and kurtosis?

I have data in the following form: Day Kurtosis Skewness Total Inflows 163 .3 .5 435670 I'm attempting to do some modeling of an inflow ...
0
votes
0answers
65 views

Skew normal approximation of Poisson distribution

What is the skew normal approximation to Poisson($\lambda$)? Am I doing this wrong?
0
votes
0answers
35 views

selecting the bins for extremely skewed data

I have a data that exhibits nearly a power law distribution, and I want to know a good binning technique to summarize the statistics. For example consider the following data: $$ \begin{array}{rr} ...
1
vote
2answers
34 views

Match Right Skewed Distribution to Normal

I am running a simulation. One of my parameters is sampled from a normal distribution. I would like to perform a sensitivity analysis using a right skewed distribution. This is what I had hoped to ...
1
vote
0answers
53 views

Probability distribution for right skewed data

My question is very similar to this previous post. I'm searching for the right distribution family to use in a GAM. My data are disease occurrence on benthic organisms (continuous response variable) ...
1
vote
0answers
46 views

Left skewed distribution implementation generalized linear model

I am very new to modelling and I have a question. I am using a generalized linear model (glm) for my data in R. My response variable is however skewed to the left ...
0
votes
0answers
20 views

Is binning a skewed Likert scale variable justifiable?

I have recently advised some colleagues on the malpractice of binning a continuous variable, which was used in order to put it as a covariate in a regression model and retained as a significant ...
4
votes
0answers
46 views

Algorithms for data symmetrization

There are statistical methods (e.g. by Box-Cox or Yeo-Johnson, see references below) to automatically bring data vectors as close as possible to symmetry/normality using optimal power transformations. ...
1
vote
1answer
27 views

Is there a negative impact from imbalance/skew in predictor variables?

I understand that imbalance or skew in the target variable within your training data can negatively impact effectiveness. Does the same apply to the predictor/independent variables? ...
2
votes
1answer
50 views

Difference of two independent gamma distribution

Given two independent random variables $X\sim\Gamma(s,r)$ and $Y\sim\Gamma(t,u)$, what is the distribution of the difference, i.e. $D=X−Y$? I assume that $s$ and $t$ are integers. How can I obtain the ...
0
votes
1answer
59 views

Transformation for negative skewness data

My analysis involved some behavioral data on swine. One measure we had was standing time (min) for pigs using accelerometers. Using SAS, I checked for normality, and results showed data to be ...
0
votes
1answer
41 views

Good references for dealing with highly skewed data

I'm looking for a good book that explains how to deal with highly skewed data (regression analysis). Could someone give some hints?
13
votes
3answers
797 views

How to assess skewness from a boxplot?

How to decide skewness by looking at a boxplot built from this data: 340, 300, 520, 340, 320, 290, 260, 330 One book says, "If the lower quartile is farther from the median than the upper quartile, ...
0
votes
0answers
31 views

Robust estimator of mean for skewed data

For heavy-tailed symmetric data, a trimmed mean or other robust estimator of the mean could be a better estimator of the mean than the sample mean. The trimmed mean will be biased for a skewed ...
0
votes
0answers
46 views

How to decide and calculate the skewness of an asymmetric confidence interval around a mean or a mean difference?

I wonder how statistical programs decide to skew the confidence interval? (I mean the confidence intervals for the means, or for the mean differences). How do they decide on the extent of this ...
1
vote
1answer
34 views

how to transform data of two experimental groups? one is positively skewed and one is negatively..

I have two experimental groups. Then I test their normality respectively. Result shows that one is positively skewed and the other is negatively skewed. In this case, how should I do the data ...
1
vote
1answer
72 views

How to model a skewed Student's t disribution

I have a small number of samples (5) of a large population (~10,000). The samples are percentages and hence I know from the context that no answers are possible below 0% or above 100%. From this one ...
0
votes
1answer
36 views

Forecasting discrete non normal data

Today I was thinking about how one would treat what I'm guessing must come up constantly in statistics so apologies if it's trivial. Some statistics such are easy to forecast, such as length, thanks ...
2
votes
1answer
77 views

Can I use the chi-squared test of independence with skewed data?

I have two variables, both categorical, one with skewed responses. How do you deal with skewed data in the chi-squared test? Are there any other relevant tests? I want to perform the test in SPSS.
0
votes
0answers
45 views

Model choice for nonnegative and positive continuous right skewed outcome

I am trying to analyze a set of nonnegative continuous non-integer data (i.e. the data points are not counts) that are mostly between 0 and 3 whose distribution is highly right-skewed even after log ...
0
votes
0answers
26 views

Analyzing the shape of distribution on a histogram [duplicate]

I have three different histograms which are generated from one sample. In each of the histograms, both variables are the same. Although binwidths for each histogram is different. By looking at each of ...
2
votes
1answer
18 views

Distribution heavily stacked on either limit - appropriate test?

I have two sets of results from an experiment that produces distributions with extremely heavily stacked sides and mostly uniform elsewhere. The aim of my analysis is to answer a the question roughly ...
4
votes
0answers
56 views

Visualizing many left-skewed distributions

I have a series of left-skewed/heavy tailed distributions that I would like to show. There are 42 distributions across three factors (labeled as A, ...
1
vote
2answers
55 views

Appropriate distribution for bounded data set

I am designing a points-scored test. There is a limit on the maximum amount of points possible, as well as on the fewest amount of points possible. I have had a test group take the test and graphed ...
5
votes
1answer
62 views

Statistical tests for comparing a skewed clinical sample

I recently surveyed 350 low-income families -- they were randomly split into two groups: control and treatment. One of the variables I am very interested in is the amount of savings of each family. ...
0
votes
1answer
67 views

Is skewness always bad?

In my experiment, I hypothesised that individuals in one treatment condition would give higher values on a likert scale than individuals in the other treatment condition. It was a one tailed ...
8
votes
4answers
3k views

Real life examples of distributions with negative skewness

Much along the lines of the "real-life examples of common distributions" I'm interested if anyone has any pedagogical examples used to teach negative skewness? There are plenty of canonical examples ...
0
votes
1answer
98 views

Single-pass algorithm for kurtosis

Here is a simple test I've run on MATLAB to check the validity of a single pass (online) algorithm for computing $3$rd moment and $4$th moment. ...
4
votes
2answers
200 views

extremely left-skewed response variable - how do I model this dataset?

This is a histogram showing my response variable. The response is # (or proportion? or percent?) of aphids eaten off of cards in fields, to model predation by natural enemies. Predictors: fixed ...
2
votes
1answer
67 views

Taylor expansion to contain sample mean, sample variance, sample skewness, and sample kurtosis

I have the following expression: $$\frac{1}{p} \ln\left(1+\frac{p^1}{1!n}\sum_{i=1}^n x_i + \frac{p^2}{2!n} \sum_{i=1}^n x_i^2 + \frac{p^3}{3!n} \sum_{i=1}^n x_i^3 + \frac{p^4}{4!n} \sum_{i=1}^n ...
1
vote
2answers
460 views

Transforming extremely skewed distributions

Assume that I have a variable whose distribution is skewed positively to a very high degree, such that taking the log will not be sufficient in order to bring it within the range of skewness for a ...
0
votes
0answers
15 views

Multivariate skew normal [duplicate]

In the maximum likelihood estimation of Skew Normal, how does R calculate the mean? You know the formula is \begin{equation} \mu=\frac{ \sum_{i} x_{i} W(x_{i})}{\sum_{i} W(x_{i})} \end{equation}. ...
3
votes
2answers
897 views

Calculating statistical significance with unequal sample sizes and unequal variances

I have two samples, one with $n_1 = 41,000$ and the other with $n_2 = 881$; the larger sample has a standard deviation of $13.74$, and the smaller has an $SD=10.75$. The means are different, and when ...
2
votes
1answer
140 views

Estimating parameters for univariate skew t

How can I solve the MLE for the skew-t distribution via EM? I am comfortable with the EM methods for t, so could someone show it for the skew-t?
1
vote
1answer
181 views

Parameter estimates for skew normal distribution

What are the formulaic parameter estimates for the skew-normal? If you can, the derivation via MLE or Mom would be great too. Thanks Edit. I have a set of data for which I can tell visually by plots ...
0
votes
0answers
11 views

SNEP distribution fitting and parameter estimates

I'm looking to try and fit a SNEP distrib to some data but am not sure how to go about this - can anyone give me some derivations for parameter estimates etc?
2
votes
2answers
149 views

Skewness adjusted t-stat

I've some data that is divided into a series of groups and am testing whether the mean is different from 1. The data is highly skewed, with skewness ranging from 1.10 to 26! I did a one-sample t-test ...
1
vote
0answers
49 views

Summing Transformed Variables

I am using regression, and trying to create a construct. I have two continuous variables but they are each skewed/not normally distributed. I have $\log_{10}$ transformed each of them separately. Is ...
1
vote
1answer
97 views

Do all these estimates of kurtosis and skewness have the same (asymptotic) distribution under normal sample distribution?

I have seen five types of estimates of kurtosis and skewness: three from http://stats.stackexchange.com/a/84057/1005 one from page 9 of Analysis of Financial Time Series by Ruey S. Tsay one from ...
0
votes
0answers
51 views

How to model zero-inflated continuous response using categorical predictors - preferably resulting in multiplicative parameters

I'm having trouble finding a suitable model for predicting the AVG value (revenue in cents) of a single click on a product on a large e-commerce site. (assuming a click leading directly to a purchase ...
3
votes
1answer
72 views

Consistent, non-parametric, robust (to fat tails) estimation of expected value of an asymmetric distribution

Question: Is anyone aware of a consistent, non-parametric estimator of the expected value of an asymmetric distribution that is robust to fat tails? What if we constrain ourselves to the class of ...