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Statistics, in a broad sense is a mathematical science which deals with interpretation of data that has been collected, organized, analyzed, and presented. These data will then be used as a basis for inference to make crucial decisions. It is widely used in almost every field which includes social, business, psychology, agriculture, governmental, medicinal, and environmental. Business statistics being one of them primarily seeks to give better decision making in the face of uncertainty to any organization or individual. It is the use of data analysis tools from elementary statistics in business which helps the management and business owners to come with viable strategies for their business/company. To make such decisions there are some skills that are required in forecasting, product planning, personnel management, quality control, market research, and yearly reports by the individual who is strategizing for the company. Business statistics is applied extensively in finance, marketing, production, services and operations management.
Descriptive Statistics: It is a summarization or description of a data set which collects responses or observation from an entire population or a sample. It helps in getting in depth knowledge of the data set by looking into what and why something has happened. There is also a possibility of distortion or missing out on important information in large datasets which can be limited through descriptive statistics as it can run comparisons across different units or people. The principal advantage of descriptive statistics is that it helps in simplifying large amounts of data in a practical manner and they also form a basis for almost all quantitative analysis of data along with simple graphics analysis. There are different types of descriptive statistics such as:
Inferential statistics can be distinguished from descriptive statistics as the latter simply describes the data on what it is and what it is showing. Inferential statistics on the other hand helps in reaching conclusion by inferring from the sample data to make generalizations about the population. It helps in understanding what the population is thinking beyond the immediate data alone. Hence, it is mainly use for a sample size of a large group or population to derive estimates based on hypotheses testing method. Sample data is used for inferential statistics because it is both cost effective and less tedious as compared to collecting data from an entire population. However, if the sample used is not representative of the target population valid statistical inferences cannot be made. Hence, it is important to use random and unbiased sampling methods.
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