skewness of normal distribution curve.....

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1. DIVERGENCE IN NORMALITY Two types of divergence in normal probability curve. They are- Skewness- Skewness  is a measure of the asymmetry of a distribution Kurtosis- Kurtosis  is a measure of the tailedness of a distribution. (outliers)

2. SKEWNESS A distribution is said to be skewed when the mean and the median fall at different points in the distribution, and the balance (or centre of gravity) is shifted to one side or the other- to left or right. Measures of skewness tell us the direction and the extent of skewness. In symmetrical distribution the mean, median and mode are identical. The more mean moves away from the mode, the larger the asymmetry or skewness.

3. SKEWED DISTRIBUTION NEGATIVELY SKEWED POSITIVELY SKEWED

4. POSITIVELY SKEWED ALSO KNOWN AS RIGHT SKEWED DISTRIBUTION. MEAN> MEDIAN> MODE THE RIGHT TAIL OF THE CURVE IS LONGER THAN ITS LEFT TAIL WHEN THE DATA IS PLOTTED ON A GRAPH

5. NEGATIVELY SKEWED ALSO KNOWN AS LEFT SKEWD DISTRIBUTION. MEAN< MEDIAN< MODE THE LEFT TAIL OF THE CURVE IS LONGER THAN ITS RIGHT TAIL WHEN THE DATA IS PLOTTED ON A GRAPH

6. NEGATIVE SKEWNESS The left tail is longer, the mass of the distribution is concentrated on the right of the figure. Long tail in the negative direction on the number line. The mean is also the left of the peak. POSITIVE SKEWNESS The right tail is longer; the mass of the distribution is concentrated on the left of the figure. Long tail in the positive direction on the number line. The mean is also right of the peak.

7. KURTOSIS In probability theory and statistics, kurtosis is a measure that tells us whether the data is heavy tailed or light tailed in a normal distribution. Kurtosis tells us about the peakness or flatness of the distribution. Kurtosis is basically the statistical measure that helps to identify the data around the mean.

8. Types of kurtosis Leptokurtic or heavy tailed distribution (kurtosis more than normal distribution) Mesokurtic (kurtosis same as the normal distribution0 Platykurtic or short tailed distribution (kurtosis less than normal distribution)

9. LEPTOKURTIC Leptokurtic is having very long and skinny tails, which means there are more chances of outliers. Positive values of kurtosis indicate that distribution is peaked and possess thick tails.

10. PLATYKURTIC Platykurtic having a lower tail and stretched around the centre tail means most of the data points are present in high proximity with mean. A platykurtic distribution is flatter (less peaked) when compared with normal distribution.

11. mesokurtic Mesokurtic is the same as the normal distribution, which means kurtosis is near to 0. In mesokurtic, distributions are normal in breadth and curves are a medium peaked height.