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SKEWNSS.

01. S kewness. 02. Types of S kewness. 03. Measurment of Skewness.

What Is Skewness ?. Skewness is a measurement of the distortion of symmetrical distribution or asymmetry in a data set. Skewness is demonstrated on a bell curve when data points are not distributed symmetrically to the left and right sides of the median on a bell curve. If the bell curve is shifted to the left or 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 zero skew, while a lognormal distribution, for example, would exhibit some right skew..

Measures of Skewness. The statistical technique to indicate the direction and extent of skewness in the distribution of numerical values in the dataset . A frequency distribution of the set of values that is not Symmetrical(normal) is called asymmetrical or skewed.

Types of Skewness. Positive Skewness. Negative Skewness.

Positive Skewness. Positive skewness occurs when the distribution has a long tail on the right side . The majority of the data points are concentrated on the left side of the distribution, while a few extreme values pull the mean and median to the right . In a positively skewed distribution, the mean is usually greater than the median . Examples of positive skewness can be found in income distributions, where a few high earners can significantly affect the overall average ..

Negative Skewness. Negative skewness is the opposite of positive skewness . It occurs when the distribution has a long tail on the left side . Most of the data points are clustered on the right side of the distribution, and a few extremely low values pull the mean and median to the left . In a negatively skewed distribution, the mean is typically less than the median . An example of negative skewness could be found in exam scores, where a few students perform extremely poorly, affecting the overall average ...

Zero (No) Skewness. A distribution is considered to have zero skewness when it is perfectly symmetric . In a symmetric distribution, the mean and median are equal, and the data is evenly distributed around the center . Examples of distributions with zero skewness include the standard normal distribution and a balanced coin toss . Skewness provides valuable information about the shape and characteristics of a dataset, helping analysts and researchers understand the underlying patterns and behaviors of the data..

Measures of Skewness. The statistical technique to indicate the direction and extent of skewness in the distribution of numerical values in the dataset . A frequency distribution of the set of values that is not Symmetrical(normal) is called asymmetrical or skewed..

Formula of Skewness.

Application of Skewness. Skewness provides an idea about the direction of outliers whether it is right side or left sideof the distribution . It measures the symmetry of the distribution. Skewness is useful in obtaining approximate probabilities and quantiles of distributions . It is used for better examining the likelihood of events falling in the tails of a probability distribution ..

Manohar Ghuge FE25 Aditya Gavhane FE05 Sanika Dumbre FE26 Aishwarya Pansare FE11 Sahil Walunj FE34 Shrijeet Jagdale FE29 Jay Navle FE27 Shrikrushna Kale FE32.

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