Tagged Questions

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

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46 views

How to transform continuous data with extreme bimodal distribution

Is there a way to transform a continuous predictor variable (grant) that has a bimodal distribution into a normal distribution (see density plot below)? I have tried log(x+c), z-score and inverse ...
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0answers
17 views

Existence of a specific linear combination of independent random variables (stochastic representation of the flexible skew normal)

Suppose to have two standard normal variables $X$ and $Y$. I would like to find something as $Y= aR+\sum_{i=1}^k b_kC_k$ (1) (k can be 1,2 or whatever) where $a,b_1, \dots , k$ are appropriate ...
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0answers
35 views

ANOVA comparing transformed data (with a constant) and untransformed normally distributed data

I am using an ANOVA to compare a number of outcome measures. Some of these are skewed and I've used a log10 transformation for them. As some of the values are zeros I've also added a constant of 1 in ...
6
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1answer
128 views

Should additional crime reports about someone change our level of doubt about an initial crime report?

Edit: Note that this question is not about multiple unreliable witnesses to the same incident, but rather multiple incidents with only one witness each. Should the accumulation of separate alleged ...
2
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1answer
47 views

More flexible bell shape than log normal distribution

I am looking for a very flexible bell shape function, with asymmetry on both sides of the bell, also with the possibility that the left arm of the bell had a milder slope while the right had a steep ...
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0answers
21 views

Should a BoxCox transformation to normalize the skewness of data be applied to all the predictors?

If there are few predictors that are highly skewed among a larger set of predictors in case of a linear regression problem, should a BoxCox transformation be applied to only these few predictors or ...
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0answers
15 views

When to use skew normal regression via MCMC (mixture models)?

when do i use skew normal or skew t Regression via MCMC? Do I use them when the data are heavily skewed, for example income data? Or do I fit a normal Regression model first and inspect the residuals ...
2
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2answers
168 views

When can a continuous variable be treated as categorical?

I have a continuous variable, which can take any value between 0 and some large, though not infinite, number. Let us assume that the maximum possible value is 1000. The values are nowhere near ...
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0answers
14 views

How to approach logistic regression on skewed dataset [duplicate]

I have a dataset with about 1M negative examples and 4700 positive examples. I'm trying to create a classifier that tries to predict the % of an example being positive. Given how much the data is ...
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0answers
28 views

GEE with exchangeable working covariance vs. GLM and using Clustered Robust standard errors?

I'm analysing a dataset including 100 individuals. These 100 individuals provided self-reported depression sores on equally spaced 4 occasions (every three months). The main independent outcome is ...
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0answers
18 views

Estimating necessary sample size

I am pretty new to statistics and I'd like to get pointers on the correct way to do this. I have a dataset in which I'm interested in the 50th and 90th percentile. I'd like to take a sample of that ...
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0answers
37 views

CDFs for Right-Skewed Distributions

How does one determine the percentage of a sample less than or equal to some x value for a set of discrete data that appear to be right-skewed? For example, I have a number of data points, and if I ...
2
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1answer
39 views

Upper bound for asymmetry using skewness

Can the following quantity be upper bounded by the (standardized third moment) Skewness of $X$ ($\mu_3/\sigma^3$)? $$\left|\mathbb{P}(X \geq \mathbb{E}X) - \mathbb{P}(X \leq \mathbb{E}X)\right|$$ I ...
2
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1answer
20 views

Percentage Beyond a Given Value for Empirically Defined Distribution

It is my understanding that standard deviation does not work well as a measurement for distributions that are heavily skewed. If I have a heavily right-skewed distribution, should I simply use the ...
0
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1answer
47 views

Regressions with long-tail variables (GDP, etc)

It seems common to apply standard linear regression to variables with long-tail distributions, like GDP, by first taking the log. What is the justification for doing that? Is it effectively assuming a ...
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0answers
31 views

GEE model for repeated skewed outcome and group mean centered time varying covariates

I have used GEE approach (log link with gamma distribution) to explore factors that are associated with outcomes of interest. My primary outcome of interest is highly skewed costs associated with an ...
2
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2answers
97 views

Skewness of a random variable that have zero variance and zero third central moment

If I have a random variable $x$, and the only information I know about it are: $$ m_1=E[x]=c, \mu_2=var(x)=0, \mu_3=E[(x-m_1)^3]=0$$ Can I conclude that the function distribution is symmetric about c? ...
8
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1answer
280 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?
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35 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 ...
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0answers
23 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
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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
46 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 ...
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0answers
28 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 ...
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2answers
66 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
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3answers
125 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 ...
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0answers
23 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
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0answers
63 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 ...
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0answers
78 views

Skew normal approximation of Poisson distribution

What is the skew normal approximation to Poisson($\lambda$)? Am I doing this wrong?
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0answers
53 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
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2answers
57 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
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0answers
88 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
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0answers
101 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
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0answers
41 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
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0answers
52 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. ...
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1answer
46 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
65 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 ...
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1answer
90 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 ...
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3answers
4k 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, ...
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0answers
50 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
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0answers
76 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 ...
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1answer
52 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
99 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
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1answer
42 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
114 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.
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0answers
69 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
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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
20 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
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0answers
73 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
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2answers
64 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 ...
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votes
1answer
85 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. ...