Kim Jae-min: Major League Baseball Statistics
Although digital platforms like Facebook, Twitter, and Amazon are coming into the deep-income world and are increasing the value of data use, math and statistics have not really started to analyze data. The Big Data Access Wall is now going up one step further because of the difficulty of extracting new meanings from the text data beyond the stereotyped number data. If you're dealing with big data analysis with the most popular professional sports in Korea, baseball, you can see that the data is new. Major League has been starting with statisticians for the last 140 years, collecting more than possible baseball data from the late 1990s, Quastec, PTQf/x, and trackman platforms, which are partnerships with Amazon in the '20s. Using the power of the long Mayr League data, we model and test baseball stories directly through traditional analysis of correlations, dispersal analysis, re-inflict analysis, back - or digital feedback, compensating with the best of the sciences of the field and the latest machine processing. All the work uses Open Source Statistics R, which is already centered on academic and industrial analysis. The goal is to model and predict reality through data, extract information and meaning from data, and make reasonable decisions that overcome human cognitive limitations. The global process strategy that must be followed to achieve the goal of analysis is more important than data analysis and requires more ideas.
Korean title: 메이저리그 야구 통계학
Korean author: 김재민
Korean publisher: 에이콘출판
ISBN-13: 9791161755236
