How have mathematical expectation concepts been applied in real-world data analysis?
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Mathematical expectation concepts have been applied in real-world data analysis in various fields. For example, in the automobile industry, data analysis has been used to make decisions regarding new factory locations and to improve human resources, accounting and finance, product design and development, supply chain and logistics, sales and marketing, and support services . In the field of spatial data classification, the mathematical expectation theory has been used to optimize the classification method by obtaining mapping value features and determining the classification of data based on parameter coordinates . Additionally, mathematical expectation has been applied in resolving economical decision questions, such as investment decision and sales profits, using mathematical statistics methods and finite difference theory . These applications demonstrate the importance and effectiveness of mathematical expectation in analyzing and making decisions based on real-world data.
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Open access•Journal Article 2 Citations | The paper discusses the application of mathematical expectation in the economical field, specifically in investment decision and sales profits. It does not provide information on the application of mathematical expectation in real-world data analysis. |
| The paper does not mention the application of mathematical expectation concepts in real-world data analysis. | |
| The paper does not mention the application of mathematical expectation concepts in real-world data analysis. | |
1 Citations | The paper discusses the application of mathematical expectation in various real-life scenarios such as insurance, investment decision, profit on sales, customer service period of service, and medical laboratory. |
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