Shree GaneshA Statistics

Moment, Skewness and Kurtosis Moment, Skewness and Kurtosis Introduction In statistics, we often use measures like mean, median, and mode to find the center or typical value of data. We also use range, variance, and standard deviation to understand how spread out the data is. However, these measures do not tell us everything about the shape of the data. To fully understand the data’s distribution, we need to look at its shape, skewness, and kurtosis. Moments help describe various aspects of the data distribution beyond just the center and spread. Skewness tells us if the data is asymmetric, meaning it leans more to one side — left or right. Kurtosis describes how peaked or flat the data distribution is and shows the presence of extreme values or outliers. By studying moments, skewness, and kurtosis, we get a better idea of how the data behaves, which helps in choosing the right statistical tests, making better vi...

  Practical No. 5:   Graphical representation of data by using Ogive Curves and Locating Quartile Values. Ogive Curve: If we plot frequencies against the value, we get the frequency curve. If instead of plotting frequencies we plot cumulative frequencies to get an ogive curve.            In frequency curve we plot the frequencies against the value of the variable but in An ogive curve is obtained by plotting the cumulative frequency against the Class limits. There are two type of cumulative frequencies i.                     Less than cumulative frequency ii.                   Greater than cumulative frequency So we get two type of the ogive curve or cumulative frequency curves as i.          ...