Applied Statistics
Statistics was classified in terms of two phases namely Theoretical and Applied Statistics. Theoretical statistics, also called as mathematical statistics, mainly involves the derivation of statistical theorems, development of standard formulas, rules and laws to be used for solving many real-world problems. Applied statistics are mainly deals with the applications of theorems and related concepts developed in theoretical statistics in the area of Business, Research and Development Units, Government Sectors, Marketing Research, Clinical Trials, and so on. According to the theory of statistics, the applied statistics are divided into two categories namely, (i) Descriptive Statistics and (ii) Inferential Statistics.
Descriptive Statistics: Most of the datasets, in its original form, are mostly very large and cannot be directly used for drawing conclusions or making decisions. In order to draw conclusions about such huge data, it is appropriate to calculate descriptive statistics to describe the basic characteristics of the data. The descriptive statistics includes summary tables and graphs/charts, where the summary tables will include certain numerical measures such as mean, median, mode, standard deviation, percentiles and so on, while the graphs/charts includes bar chart, pie chart, histogram, scatter plot, line plot and so on.
Inferential Statistics: If a set of measurements given in the dataset is the entire population, then the conclusion about the dataset has to be drawn only based on the descriptive statistics. However, it not easy to examine the entire population as it is very expensive and time consuming to enumerate the whole population. Due to these reasons, only a small part of the population (usually called a sample) would be considered to answer questions about the whole population. The branch of statistics that deals with making conclusion about the whole population based on the corresponding sample information is called Inferential Statistics. The goal of the inferential statistics is to make inferences about the population characteristics based on the analysis of sample data drawn from this population.
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