Importance of Statistical Inference Inferential Statistics is important to examine the data properly. To make an accurate conclusion, proper data analysis is important to interpret the research results. It is majorly used in the future prediction for various observations in different fields. It helps us to make inference about the data. The statistical inference has a wide range of application in different fields, such as: Business Analysis Artificial Intelligence Financial Analysis Fraud Detection Machine Learning Share Market Pharmaceutical Sector
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Operational Research (OR) is the application of similar ideas to larger, more complex decisions that concern the operations of systems, such as businesses and networks of machines. Making these decisions using OR entails employing mathematical methods in order to solve a numerical version of the problem at hand. The objective or goal is the first thing that needs to be understood in OR, as it describes what we want out of a solution and lets us compare different ones. The objective is normally quantifiable, such as profit or cost. In problems of a complex nature, it helps to find ways to represent other parts of the system numerically. OR involves doing exactly this, through analysing the system's structure and components in order to extract as much numerical information as possible. Many properties of a system can be quantified, such as resources available to it, its energy efficiency, the size of its workforce and so on. Through doing this, these properties become easily compar