Statistical Data Analysis plays a key role in promoting the Sustainable Development Goals (SDGs). Through examining actual data for statistical analysis, it not only allows for a scientific understanding of uncertainties in real-world phenomena and describes trends but also evaluates policy effectiveness, providing strong data support for decision-making. The following examples illustrate the relationship between statistical data analysis and the various SDG targets:

1. Descriptive Statistics:

• Widely applied to summarize the basic characteristics of data and present distribution patterns, which are crucial for public policy issues related to scientific development, health, education, environment, and government governance.

• SDG Connection: Used to measure literacy rates (SDG 4), the proportion of people living in poverty (SDG 1), water resource coverage (SDG 6), and more.

2. Hypothesis Testing and Inference:

• Application: Inferring the distribution and characteristics of a population from sample data, conducting hypothesis tests for parameters, and estimating confidence intervals, or comparing differences among various groups.

• SDG Connection: Assessing policy effectiveness, such as testing whether health intervention measures reduce disease transmission rates (SDG 3) or whether education reforms significantly enhance student performance (SDG 4).

3. Regression Analysis:

• Exploring relationships between variables, which can be applied to predictions.

• SDG Connection: Analyzing the relationship between economic growth and poverty rates (SDG 1 & SDG 8), predicting the impact of carbon emissions on climate change (SDG 13).

4. Clustering & Classification:

• Applied to categorize data into subgroups with similar characteristics, which is useful for identifying groups with different traits, targeting specific issue groups, or building more accurate predictive models.

• SDG Connection: Analyzing health risk characteristics in different communities (SDG 3) or classifying which areas most urgently need to promote clean energy policies (SDG 7).

The Department of Statistics offers a course on [Statistical Data Analysis] every semester. This course serves as an introductory course in data analysis and is a required course for the [Data Science Specialization] and an elective course for the [Data Science Credit Program]. In today’s data-driven world, the content of this course has become an essential part of higher education general studies.