Statistics and Sampling
Statistics and Sampling are the techniques in which statistics summarizes the data or is the science that assembles, introduces, examines and clarifies or explains the numerical data and sampling is used to collect the require data from the summarized collection of data. Statistics is used when we have large number of data not when we have a single figure.
Statistical Sampling is the process or strategy in which the data is collected from somewhere then it analyzed using tables and graphs by doing this we can identify the how many attention of a occurrence are essential in order to draw fairly legal results about it.
In general Statistics sampling is related with the choosing of a subset of singles from within a population so that we can calculate the feature of the whole population. Sampling has three advantages : -
-Low cost during the retrieving the data.
-Faster data collection.
-After the sampling of data we get the summarized data so that the accuracy and quality is retain.
Need of sampling : - When we have scattered data then it is summarized by the statistics into a proper manner then it is retrieved by the sampling methods and techniques. Like in population it is not easy to check the every element. So for these cases some elements are chosen from the population in such mode so that they can denote for universe. This type of segment is called sample and the process is called sampling. Mean, median, mode and range are used in sampling. There are lots of techniques and methods that simplify the process of sampling, they are :- (know more about icse board, here)
-Random Sampling.
-Systematic Sampling.
-Opportunities Sampling.
-Stratified Sampling.
-Probability Proportional To Size Sampling.
-Cluster Sampling.
-Quota Sampling.
-Accidental Sampling.
-Line Intercept Sampling.
-Panel Sampling.
By all these methods we can sample any type of data and In the next session we will discuss about Statitics and its Applications.