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If the mean is greater than mode the distribution is positively skewed.if the mean is less than mode the distribution is negatively skewed.if the mean is greater than median the distribution is positively skewed.if the mean is less than median the distribution is negatively skewed.

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Noor Fatima 226

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4y ago
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Samra khalid

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4y ago

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The effect of skewness on specific level maximum likelihood test statistics based on normal theory in multilevel structural equation model. Structural equation modeling has become an important and widely used analysis approach in social and behavioral science.

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Musfira Naveed

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If skewness is positive, the data are positively skewed or skewed right, meaning that the right tail of the distribution is longer than the left. If skewness is negative, the data are negatively skewed or skewed left, meaning that the left tail is longer.

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laraib gujjar

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In this study it is researched how statistical power is affected in nonparametric tests. For this purpose, from the

nonparametric tests used for testing the data obtained from two independent samples, Kolmogorov-Smirnov two

samples (KS-2) test are selected. The study intends to establish a guide for the researchers who are willing to

perform analysis by using skewed data in case of fixed kurtosis.

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Ayesha Mehmood

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4y ago

Skewness refers to distortion or asymmetry in a symmetrical bell curve, or normal distribution, in a set of data. If the curve is shifted to the left or to the right, it is said to be skewed. Skewness can be quantified as a representation of the extent to which a given distribution varies from a normal distribution. A normal distribution has a skew of zero, while a lognormal distribution, for example, would exhibit some degree of right-skew.

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Hina Hameed

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4y ago

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The maximum likelihood (ML)method based on the normal distribution assumption ,is widely based in mean and covariance structure analysis .with typical nonnormal data , the ML method will lead to baised statistics and inappropriate scientific conclusions .

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laraib gujjar

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Anonymous

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Zarish Fatima

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If there are too much skewness in the data, then many statistical model don't work. So in skewed data, the tail region may act as an outlier for the statistical model and we know that outliers adversely affect the model's performance especially regression-based models. In the case of a right-skewed parent population, a shift to the left will decrease skewness in the sampling distribution of the t-statistic, whereas a shift to the right will increase the skewness coefficient of the sampling distribution of the t-statistic. The power of the t-test isn't necessarily diminished in the absence of normality.

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Anonymous

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4y ago

Skewness tells us more precious evaluation about the sample. If there is the bigger number then its mean there is more probability of skewness. If that is small in number then its means it has less distortion in the sample.

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Anonymous

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(18-246)Arfaat Asghar

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Real life distributions are usually skewed. If there are too much skewness in the data, than many statistical model dont work properly.

In skewed data, the tail region may act as an outlier for the statistical model and we know that outliers adversely affect the model 's performance especially regression-based models.

There are statistical model that are robust to outlier like a Tree-based models but it will limit the possibility to try other models. So, it is necessary to transform the skewed data to close enough to a Gaussian distribution or Normal distribution.

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Q: How skewness can effect on analysis of a study?
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