Spreadsheets and Basic Data Analysis

2020 ◽  
pp. 314-339
Author(s):  
Bruce Garrison
Keyword(s):  
Data Analysis ◽  
Basic Data

Basic Data Analysis for Quantitative Research

2019 ◽  
pp. 326-352
Author(s):  
Joe F. Hair ◽  
Michael Page ◽  
Niek Brunsveld
Keyword(s):  
Data Analysis ◽  
Quantitative Research ◽  
Basic Data

scholarly journals Data Wrangling and Management in R

2017 ◽  
Author(s):  
Nabeel Siddiqui
Keyword(s):  
Data Analysis ◽  
Basic Data ◽  
R Packages

This tutorial explores how scholars can organize 'tidy' data, understand R packages to manipulate data, and conduct basic data analysis.

scholarly journals Data analysis of financial burden index through KBO league FA pitcher's performance and contract amount size

2021 ◽  
Vol 11 (3) ◽  
pp. 2555
Author(s):  
Semin Kim ◽  
Kangsoo You
Keyword(s):  
Data Analysis ◽  
Economic Crisis ◽  
Financial Burden ◽  
Basic Data ◽  
Professional Baseball ◽  
Sports Industry ◽  
Sports Events ◽  
The World ◽  
The Republic ◽  
Baseball Fans

Due to the recent pandemic of COVID-19, sports events around the world are being hit hard in 2020. However, with the KBO league having been opened even though it is late, it has attracted the attention of baseball fans around the world as it becomes an overseas broadcast. However, since the Republic of Korea is also affected by the global economic crisis, the financial burden of professional baseball teams that rely on their parent company has become a hot topic. Therefore, in this study, we collected records such as IP, ERA, and WAR of KBO league FA pitchers and news related to FA contracts. Then, we preprocessed the data and analyzed it. To this end, we analyzed the performance and financial burden indicators according to the pitcher's age and contract years. In addition, it was found that the performance of athletes was maintained until their mid 30’s, and through rational FA contracts, the team and athletes were able to suggest win-win strategies. And with this basic data analysis in the sports industry, the possibility of utilizing these strategies was confirmed.

The purpose of this study is to provide basic data for Korean companies to enhance the sports sponsorship effects and market competitiveness in China. In order to achieve the goal, fans of Jiangsu Suning Professional Soccer of China, whose main sponsor was Samsung Electronics, were selected as subjects. A total of 250 questionnaire were used for the final data analysis. The model and hypothesis were tested using AMOS 22.0 statistical package. The results were as followed. First, the team identification had a positive impact on the sponsor identification. Second, team identification had a positive impact on the professional soccer-sponsor fit. Third, team identification had a positive effect on the sponsor’s attitude. Fourth, sponsor identification had a positive effect on the sponsor’s attitude. Fifth, professional soccer-sponsor fit had a positive effect on sponsor attitude. Sixth, sponsor attitude had a positive effect on the sponsor image. Seventh, the sponsor image had a positive effect on the intention of purchasing the sponsor product. It indicated that fans’ team identification in Jiangsu Suning Professional Soccer influenced sponsor identification and professional soccer-sponsor fit, resulting in a positive sponsor attitude, sponsor image, and intention of purchasing the sponsor product. Therefore, it was important for sports marketers to reinforce the value of team identification and sponsor identification to enhance sponsorship effect and increase professional soccer-sponsor fit.

2020 ◽  
Vol 59 (5) ◽  
pp. 87-102
Author(s):  
Feng Yin ◽  
Kwang-min Cho ◽  
Hyun Byun
Keyword(s):  
Data Analysis ◽  
Positive Impact ◽  
Basic Data ◽  
Team Identification ◽  
Professional Soccer ◽  
Market Competitiveness ◽  
Final Data ◽  
Sports Sponsorship ◽  
Positive Effect
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