Statistical Analysis on the Book Borrowing Quantity of University Library—Taking Qilu University of Technology as an Example
- DOI
- 10.2991/assehr.k.201214.023How to use a DOI?
- Keywords
- Library Borrowing Loan Amount, Deterministic seasonal model, ARIMA model, Possion log-linear model
- Abstract
According to the library book borrowing amount data from June 2013 to December 2018 at Qilu University of Technology (Shandong Academy of Sciences), this work studied the statistical laws of data series of borrowing quantity. Based on the combination of seasonal effects, long-term trends, and random factors, a deterministic seasonal model and an ARIMA seasonal model were established for the loan quantity series. The modeling and simulation obtained well-fitting and forecasting effects, and the borrowing quantity showed periodic fluctuation and rising slowly. Furthermore, a possion logarithmic linear model was established to obtain a significant difference between male and female students in different grades. The results disclosed that the volume of books borrowed is lower in freshman, higher in sophomore and junior, and lower in the senior year. Besides, female students generally borrow more books than male students. The research results are expected to offer a useful reference for researchers majoring in book management.
- Copyright
- © 2020, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yulin Huang AU - Zhongshang Liu AU - Yongxue Liu AU - Wenrui Qu PY - 2020 DA - 2020/12/16 TI - Statistical Analysis on the Book Borrowing Quantity of University Library—Taking Qilu University of Technology as an Example BT - Proceedings of the 2020 6th International Conference on Social Science and Higher Education (ICSSHE 2020) PB - Atlantis Press SP - 129 EP - 135 SN - 2352-5398 UR - https://doi.org/10.2991/assehr.k.201214.023 DO - 10.2991/assehr.k.201214.023 ID - Huang2020 ER -