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Measures of Skewness, Business Mathematics & Statistics Video Lecture | SSC CGL Tier 2 - Study Material, Online Tests, Previous Year

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FAQs on Measures of Skewness, Business Mathematics & Statistics Video Lecture - SSC CGL Tier 2 - Study Material, Online Tests, Previous Year

1. What is skewness in statistics?
Ans. Skewness is a measure of the asymmetry or lack of symmetry in a probability distribution. It quantifies the extent to which a distribution's tail is pulled towards one side or the other. Positive skewness indicates that the tail is longer on the right side, while negative skewness indicates a longer tail on the left side.
2. How is skewness calculated?
Ans. Skewness can be calculated using different formulas, but one commonly used method is through the calculation of the third standardized moment. This involves subtracting the mean from each data point, raising it to the power of three, taking the average of these values, and then dividing it by the standard deviation cubed. The resulting value represents the skewness of the distribution.
3. What does a positive skewness value indicate?
Ans. A positive skewness value indicates that the distribution has a tail that is longer on the right side. This means that there are more outliers or extreme values on the right side of the distribution. In other words, the majority of the data is concentrated towards the left side, while a few larger values pull the tail towards the right.
4. How does skewness affect data analysis?
Ans. Skewness is an important measure in data analysis as it provides insights into the shape and symmetry of a distribution. By identifying whether the distribution is positively skewed, negatively skewed, or symmetric, analysts can make more informed decisions about the data and choose appropriate statistical techniques. Skewness can also affect the interpretation of summary statistics such as the mean and median.
5. Can skewness have a value of zero?
Ans. Yes, skewness can have a value of zero. A skewness value of zero indicates that the distribution is perfectly symmetrical, with equal amounts of data on both sides. This means that the mean, median, and mode would all be the same. However, it is important to note that a skewness value of zero does not necessarily imply a normal distribution, as other factors need to be considered for that determination.
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