⏳ Mining deep into Data Mining - Statistics - PART II ⏳
Before analyzing distributions in statistics, Let's understand the required essential basics 💭 MEAN Mean is an essential concept in statistics. In common terms, it can be defined as the average of a collection of values. It can be referred to as central tendency or centrality for a probability distribution. Thus, it basically denotes the centrality of a series of values. 💭 STANDARD DEVIATION A standard deviation is a statistic that measures the dispersion of a dataset relative to its mean. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. 💭 VARIANCE Variance is the measure of how well the data is dispersed from the existing data points. (ie) the mean squared difference between every data point and the center of distribution (mean). This yields the rate of dispersion of data points. Variance is also the square of standard deviation. For example, let's consider a series of price list valu