Applied Statistics
应用统计学是工业工程专业的重要基础课程，侧重于统计方法在工程和管理问题中的实际应用。课程内容包括描述性统计、参数估计、假设检验、方差分析、回归分析、实验设计、非参数统计和统计质量控制等。学生将学习使用Minitab、R或Python进行数据分析，掌握从数据收集、整理、分析到得出结论的完整统计思维过程。
Applied Statistics is an important foundational course in industrial engineering, focusing on the practical application of statistical methods to engineering and management problems. Topics include descriptive statistics, parameter estimation, hypothesis testing, analysis of variance, regression analysis, experimental design, nonparametric statistics, and statistical quality control. Students learn to use Minitab, R, or Python for data analysis and develop statistical thinking from data collection to conclusion.
选择一个实际生产或服务过程作为研究对象，设计正交实验或全因子实验，考察温度、压力、速度、材料等多个因素对产品质量指标或生产效率的影响。收集实验数据，使用方差分析和回归分析方法识别显著因素，建立预测模型，并提出工艺优化建议。要求使用Minitab或R完成全部统计分析。
Select an actual production or service process as the research subject. Design an orthogonal experiment or full factorial experiment to investigate the effects of multiple factors such as temperature, pressure, speed, and materials on product quality indicators or production efficiency. Collect experimental data, use ANOVA and regression analysis to identify significant factors, build a prediction model, and propose process optimization recommendations. Complete all statistical analysis using Minitab or R.