在体育资金方面的基于证据的政策制定,使用数据驱动的优化方法
Jan Hurt1, Liuhuaying Yang1, Johannes Sorger1
1Complexity Science Hub, Vienna, Austria.
PloS one
|December 31, 2024
概括
最佳地分配政府资金给体育俱乐部,考虑到区域社会经济因素,可以显著地促进儿童的发展.
科学领域:
- 运动科学 运动科学 运动科学
- 公共政策 公共政策
- 经济学 经济学 经济学
背景情况:
- 定期体育活动对儿童发育至关重要,体育俱乐部在促进运动方面发挥着关键作用.
- 公共补贴已被证明可以增加体育俱乐部的参与率,但其有效性因地理位置和社会经济条件等因素而异.
研究的目的:
- 开发和评估一个数据驱动的模拟模型,以优化政府资金分配给体育俱乐部.
- 通过战略性金融投资,最大限度地让儿童进入体育设施.
主要方法:
- 编制了1854个奥地利足球俱乐部的数据集,包括预算,位置,会员和年龄人口统计数据.
- 开发了一个模拟模型,该模型包含了俱乐部预算和会员资格之间的亚线性关系,受社会经济因素的影响.
- 评估了各种融资策略,比较了优化方法和天真的分配方法.
主要成果:
- 确定了体育俱乐部预算和活跃会员之间的亚线性关系,根据当地社会经济条件进行调整.
- 优化战略,将资金根据区域社会经济特征和俱乐部预算进行调整,与天真方法相比,儿童参与率高达117%,使用额外的500万欧元.
结论:
- 基于证据的,个性化的公共资金策略显著提高了补贴对儿童体育俱乐部参与的影响.
- 根据区域社会经济背景和俱乐部特定需求量身定制财政支持是最大限度地提高对青少年体育的公共投资的关键.
相关概念视频
01:09Decision Making: P-value Method
5.3K
The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
5.3K
01:04Social Facilitation
31.8K
Not all intergroup interactions lead to negative outcomes. Sometimes, being in a group situation can improve performance. Social facilitation occurs when an individual performs better when an audience is watching than when the individual performs the behavior alone. This typically occurs when people are performing a task for which they are skilled.
31.8K
01:29Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
40
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
40
01:16Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data
113
Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
113
01:16Response Surface Methodology
89
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
The process of RSM involves several key steps:
89
01:14Decision Making: Traditional Method
4.0K
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
4.0K