Application of Big Data to Common Statistical Methods Based on Game Systems
Jia Shen *
School of Mathematics, Liaoning Normal University, Dalian-116029, China.
Kerui Wu
School of Mathematics, Liaoning Normal University, Dalian-116029, China.
Yiming Liu
School of Mathematics, Liaoning Normal University, Dalian-116029, China.
*Author to whom correspondence should be addressed.
Abstract
In this paper, statistical methods are adopted to analyze its role in data processing and prediction, emphasizing three statistical models of time series model, neural network model based on genetic algorithm and K-means algorithm, systematically introducing how to classify and predict data based on three common statistical methods, and find out the characteristics of data by using the trend of data change. In order to grasp the actual user and other relevant information. Taking MCM C project in 2023 as an example, this paper classifies and analyze the given data, find out the variation characteristics of variables, predicts the development and changes of variables, and provides direction for game companies to further strategies, so as to enhance users' sense of experience. Finally, through comprehensive analysis and processing, three kinds of prediction and classification statistical models are applied deeply to cope with this practical issue.
Keywords: Time series analysis, BP neural network, K-means clustering analysis, correlation analysis