应用统计专硕是当前热门的一种专业学位项目，它主要培养学生在统计学理论与应用方面的能力，具备独立分析和解决实际问题的实践能力。在选择专业时，学费是一个重要考虑因素。那么，应用统计专硕每年的学费是多少呢？

对于不同学校和地区而言，应用统计专硕的学费可能会有所不同。一般来说，学费涉及到的因素包括学校的地理位置、学校的声誉和学术实力等。在大城市和名校就读的学生，相比于在一些偏远地区或低知名度院校就读的学生，往往需要支付更高的学费。

根据我对一些知名高校的调查，应用统计专硕的学费一般在5万到15万元之间。这只是个大致范围，具体的学费标准还需要根据学校的政策来确定。另外，还有一些因素也会影响学费的高低，比如学制的长短、是否全日制等。

总的来说，选择就读应用统计专硕需要综合考虑学费及其他因素。学费只是其中的一个方面，我们还需要了解和研究学校的教学质量、导师资源、就业情况等。只有全面了解并进行对比，才能作出更好的决策。

In English:

The annual tuition fees for the Master's Program in Applied Statistics, is a popular professional degree program aimed at nurturing students' abilities in statistical theory and application, as well as their practical skills to independently analyze and solve real-world problems. When choosing a program, tuition fees are an important factor to consider. So, how much is the annual tuition fee for the Master's Program in Applied Statistics?

The tuition fees for the Master's Program in Applied Statistics may vary depending on the school and location. Generally, factors such as the geographical location of the school, its reputation, and academic strength are taken into account when determining tuition fees. Students studying in major cities and prestigious universities often have higher tuition fees compared to those studying in remote areas or lesser-known institutions.

Based on my research on some well-known universities, the tuition fees for the Master's Program in Applied Statistics generally range from 50,000 to 150,000 RMB per year. However, this is just a rough estimate, and specific tuition fee standards should be determined based on the school's policies. Additionally, other factors such as the length of the program and whether it is full-time or part-time can also affect the tuition fees.

In summary, when choosing to study the Master's Program in Applied Statistics, tuition fees should be considered along with other factors. Tuition fees are only one aspect, and we also need to understand and investigate the quality of education, mentorship resources, and employment prospects of the schools. Only through comprehensive understanding and comparison, can we make better decisions.