measures (or refers to) a degree of asymmetry in the distribution of a variable.
1
vote
1answer
46 views
Simulating multiple linear regression
I would like to simulate a multiple linear regression model using R.
If I have the skewness and kurtosis for the residuals, how can I do that?
5
votes
2answers
85 views
Median + MAD for skewed data
I am trying to figure out what happens if you apply Hampel's outlier detection technique based on the median and the MAD to data that is skewed. Apparently, the advantage of Hampel's method over ...
1
vote
2answers
98 views
Do skewness and kurtosis uniquely determine type of distribution?
Inspired by this answer, I have following question: Is it enough to know just skewness and kurtosis in order to determine distribution that data comes from? Is there any theorem that implies this? ...
0
votes
0answers
108 views
High kurtosis, skewness and outliers
Currently I am working on my master this which is about excess returns (Sharpe ratio) of Asian REITs. I just transformed all the data in variables which are ready to use in SPSS. In the panel data ...
2
votes
1answer
60 views
Principal component analysis (PCA) on long-tailed data
(1) When doing PCA, do you assume the variables to be bell-shaped? Say if I have a bunch of variables, some are bell-shaped but some have characteristic long (right) tails (highly skewed and ...
2
votes
1answer
73 views
Skewness of fitted mixture not correct?
I fitted a gaussian mixture to my financial data.
The values are:
$\pi= 0.3$
$\mu_1= -0.01$
$\mu_2= 0.01$
$\sigma_1=0.01$
$\sigma_2=0.03$
One can see, that both single distributions have a ...
3
votes
1answer
79 views
Skewness of a mixture density
I am fitting a gaussian mixture to financial data. My mixture density is given by:
$f(l)=πϕ(l;μ_1,σ^2_1)+(1−π)ϕ(l;μ_2,σ_2^2)$
I calculated the skewness of the data already. Now, I want to look at ...
0
votes
1answer
92 views
Highly skewed survey data
I've just received some survey data and I found that the results are highly positively skewed. Most of the questions were answered on a five-point Likert scale, and the mean values of many questions ...
1
vote
2answers
169 views
How to deal with extreme but “real” data, classify as outliers or no?
I have an explanatory variable, close, which is the daily close price of a firm in the stock market.
The following summarizes this explanatory variable:
...
1
vote
0answers
36 views
Calibration of probabilities in online learning (real-time learning) with Vowpal Wabbit
How exactly Real-Time Learning techniques deal with the problem of skewed distribution in dependent and independent variables? I am getting acquainted with Vowpal Wabbit and face this problem. My data ...
1
vote
0answers
46 views
Skewness in robust regression
I am doing a robust regression to predicted a left-skewed outcome. Do I still need to do a transform on my data before doing robust regression, or will that issue be taken care of by the robust ...
0
votes
1answer
82 views
Modeling a outcome variable heavily skewed toward 0
I am working with a data set to model student performance with various variables from the class/school/district/provincial level. Student performance is extremely low though--~70% of reading ...
2
votes
1answer
183 views
Skew in both directions and dealing with outliers
I have a lot of wonderfully messy data (got to love the social sciences), and realized that I was not fully prepared to bear its wrath.
For the record, after reading some articles regarding ANOVA, I ...
1
vote
1answer
60 views
positive skewness in simulation results
I am using simulations to make a calculation. I generate many random numbers from a distribution for each input and then I take the mean and standard deviation of the outputs.
I noticed that the mean ...
0
votes
1answer
216 views
how to bootstrap p-value in ttest in Stata?
Suppose I need to run ttest bhar12=0 and the output comes as:
...
2
votes
2answers
286 views
What is coskewness and how can it be calculated?
I would like to calculate coskewness of two random variables. However I couldn't find even basic information on this matter. Is there a standard definition? How to calculate it? If not what are my ...
4
votes
1answer
108 views
How do I test for a symmetric distribution?
I collect numbers from generators that yield different ranges of whole numbers with an unknown distribution. I want to estimate the mean of the numbers outputted by this generator. I'm convinced the ...
3
votes
1answer
233 views
How to create a random variables in a simulation using skewness and kurtosis as well as average and standard deviation input?
I am curious to learn whether there are any best practises in creating random variables for a Monte Carlo simulation using input such as skewness and kurtosis information of a particular distribution. ...
1
vote
1answer
94 views
Cluster analysis with skewed distibutions
For my master's thesis I would like to use different clustering algorithms to cluster municipalities (as objects) in regard to their land-use characteristics (as variables).
Analyzing my data ...
8
votes
2answers
379 views
“Peakedness” of a skewed probability density function
I would like to describe the "peakedness" and tail "heaviness" of several skewed probability density functions.
The features I want to describe, would they be called "kurtosis"? I've only seen the ...
0
votes
0answers
79 views
How can I tell whether my data is skewed due to sampling error?
I have some psychological data (N=100, 2 conditions) in which across 55 questions participants made an estimate, and then after a manipulation they made an additional estimate. I then calculated how ...
8
votes
1answer
129 views
How to handle the difference between the distribution of the test set and the training set?
I think one basic assumption of machine learning or parameter estimation is that the unseen data come from the same distribution as the training set. However, in some practical cases, the distribution ...
7
votes
2answers
324 views
Transformation to increase kurtosis and skewness of normal r.v
I'm working on an algorithm that relies on the fact that observations $Y$s are normally distributed, and I would like to test the robustness of the algorithm to this assumption empirically.
To do ...
0
votes
1answer
203 views
High kurtosis and bad skewness
Is it necessary to have normalized data if you want to apply a dynamic correlation coeffient? should the explanatory variables in the dcc method also be normalized? My dataset has a high kurtosis and ...
6
votes
3answers
258 views
Choosing c such that log(x + c) would remove skew from the population
I have data for which I would like to take the log transformation before doing OLS. The data include zeros. Thus, I want to do a log(x + c). I know a traditional c to choose is 1. I am wondering ...
0
votes
0answers
66 views
Data transformations of scales
Could really do with some help from someone with more stats expertise than I have.
I have some data relating to a customer survey along a range of measures which are consolidated into a number of ...
2
votes
1answer
130 views
Permutation test to test significance of skewness/kurtosis of two distributions?
To test the significance of the skewness difference between two distributions with $N_1$ and $N_2$ samples, would the following test work:
Create a single array of all the samples from both ...
2
votes
1answer
219 views
Does variance predict skewness?
I am trying to get some ideas on how to test for an implicit relationship, if any, between variance and skewness. That is, given a very large data set (e.g 90 years of monthly returns), is there a ...
4
votes
2answers
359 views
Skewed variables in factor analysis
I want to do principal component analysis (factor analysis) on SPSS based on 22 variables. However, some of my variables are very skewed (skewness calculated from SPSS ranges from 2-80!!!).
So here ...
4
votes
1answer
530 views
Transform continuous variables for logistic regression
I have large survey data, a binary outcome variable and many explanatory variables including binary and continuous. I am building model sets (experimenting with both GLM and mixed GLM) and using ...
2
votes
1answer
47 views
Small Sample, Low Baseline in DV, Interaction anyway?
Please assume that I have two metric independent variables (e.g., two blood parameters), and a dependent variable (e.g., a disease). On the DV, 0 represents the absence from the disease, 1 represents ...
0
votes
1answer
85 views
What is the most appropriate test for this situation?
I want to statistically test the mean difference of a continuous variable (let's call this variable 1) between four groups (nominal) in my sample. Variable 1 has a very skewed distribution.
This test ...
1
vote
1answer
152 views
Skewness in dependent variable (OLS, Gauss Markov, non-normality)
Consider the time series to be estimated with OLS:
$Y_t = a + \bf{X}_t\bf{b} + e_t$
where $Y_t$ is skewed, $\bf{X}_t$ is a vector of regressor values at time $t$, $\bf{b}$ is a vector of coefficient ...
1
vote
2answers
415 views
Do data transformations before factor analysis need to be consistent across different variables?
(This question continues the previous one)
I am creating a questionnaire, and I have identified 3 questions which are skewed (2 positively skewed & 1 negatively skewed). I successfully ...
4
votes
1answer
748 views
Are data transformations on non-normal data necessary for an exploratory factor analysis when using the principal axis factoring extraction method?
I am developing a questionnaire to measure four factors which constitute spirituality, and I would like to ask the following question:
Are data transformations on non-normal data necessary for an ...
5
votes
0answers
121 views
Gigantic kurtosis?
I am doing some descriptive statistics of daily returns on stock indexes. I.e. if $P_1$ and $P_2$ are the levels of the index on day 1 and day 2, respectively, then $log_e (\frac{P_2}{P_1})$ is the ...
1
vote
2answers
412 views
What is the correct SD to use to get a 95% CI for skewed data?
Let $X = [94, 10, 100, 100, 16, 14, 100, 100, 70, 88, 100, 100, 12, 100, 100, 58, 32, 100, 32, 36, 98, 0, 100, 100, 100]$
where $X$ are students' scores (between 0 and 100), and note many full marks!
...
1
vote
1answer
221 views
Is it necessary to log transform positively skewed DV’s even though I am using bootstrapping? [duplicate]
Possible Duplicate:
In linear regression, when is it appropriate to use the log of an independent variable instead of the actual values?
I am running a series of multiple mediation models. ...
4
votes
1answer
113 views
Eigen-vectors and skewness
I'm doing some experiments to assess the extend to which MV skewed distributions can affect eigen-vectors (and more specifically Deming regressions).
Suppose $X=(x_i,...,x_n')$ with $x_i \in ...
4
votes
2answers
312 views
How does Cornish-Fisher VaR (aka modified VaR) scale with time?
I have already posted this question in the quant section, maybe the statistics community is more familiar with the topic:
I am thinking about the time-scaling of Cornish-Fisher VaR (see e.g.page 130 ...
0
votes
0answers
114 views
How to deal with a variable that ranges from 0 to 1 and the distribution has two spikes at these values with normal-like distribution in the middle.
I have the following setting (& would like to pick a model/or transformation that can help): dv is normally distributed continuous variable, all IVs are continuous, but one of them is the above ...
6
votes
5answers
1k views
Can I hypothesis test for skew normal data?
I have a collection of data, which I originally thought was normally distributed. Then I actually looked at it, and realised it wasn't, mostly because the data is skewed, and I also did a ...
8
votes
3answers
294 views
Mean$\pm$SD or Median$\pm$MAD to summarise a highly skewed variable?
I'm working on highly skewed data, so I'm using the median instead of the mean to summarise the central tendency. I'd like to have a measure of dispersion
While I often see people reporting mean ...
2
votes
1answer
290 views
Mean squared error for data with skewed distribution
I am doing regression task and the response variables in my dataset have a skewed distribution. Say, for the sake of simplicity, that I have a model Y~X and Y(response variable) is in [1,5] but there ...
1
vote
1answer
409 views
Is Hansen's skewed-$t$ distribution the same as the skewed-$t$ distribution which is a special case of GH Distribution?
I recently studied two asymmetric t distribution both with a name of skewed-$t$. I am confused with their differences or are they actually the same?
The first one is introduced by Hansen (1994) with ...
2
votes
0answers
87 views
At which extent can standardized moment be trusted in comparison to plotting data?
Motivation
I am interested on using R to do data analysis on a considerable amount of data. Having to plot each time I want to observe if it fits any particular distribution by eyeball (which can be ...
1
vote
1answer
865 views
How can I calculate cut-off points from a normal distribution?
I'm trying to calculate the upper percentage points for the 0.99 percentile for samples drawn from a normal distribution, with a sample size of 500. How can I calculate the expected values for ...
4
votes
3answers
3k views
Why is the arithmetic mean > median on a histogram skewed to the right?
I am fairly new to statistics.
Currently I am into (histograms) medians, arithmetic mean and all the general basics.
And I came accross the fact/rule that the arithmetic mean is (always) larger than ...
3
votes
1answer
96 views
Why is the expected value of the number of trials before the first success larger than the number of trials with a 50% probability of success?
For a Bernoulli distribution with parameter p, the number of trials with a 50% probability of at least one success is about (1/p) * ln(2). But the expected value of the corresponding geometric ...
12
votes
3answers
530 views
Can somebody offer an example of a unimodal distribution which has a skewness of zero but which is not symmetrical?
In May 2010 Wikipedia user Mcorazao added a sentence to the skewness article that "A zero value indicates that the values are relatively evenly distributed on both sides of the mean, typically but not ...
