一、12204010掌握建设工程项目质量控制的概念和原理 二、12204020掌握建设工程项目质量控制系统的建立和运行 三、1Z204030掌握建设工程项目施工质量控制和验收的方法 四、1Z204040熟悉建设工程项目质量的政府监督 五、1Z204050熟悉常见的工程质量统计分析方法的应用 六、1Z204060了解GB/T19000IS9000(2000版)质量管理体系标准 七、1Z204070了解建设工程项目设计质量控制的内容和方法

1.1概率空间 1.2随机变量与分布函数； 1.3数字特征、矩母函数与特征函数 1.4收敛性 1.5独立性与条件期望

元线性回归分析估计两个变量的关 系 其中一个变量作为响应变量或输出变量 (y)o 另一个变量作为预测变量或解释变量 有时两个变量中哪一个是响应变量(例 如高度和重量)是不好区分的。在这种 情况下,可能会使用相关分析

基本名词概念 3.1分离定律 3.2自由组合定律 3.3数理统计原理在遗传研究中的应用 3.4 Mendel定律的扩展 3.5孟德尔遗传规律的意义 3.6人类系谱图式

线性回归 回顾: 线性模型:y=Xβ+E y-N(XB, o-1) 最小二乘法:B=(XXXy y=y=X的拟合值户=X(XX)Xy=Hy e=误差=残差=y-y=yy(H)y

 Formulate null (H0) and alternative hypotheses (H1) for applications involving one sample population mean or proportion  Formulate a decision rule for testing a hypothesis  Know how to use the critical value and p-value approaches to test the null hypothesis (for both mean and proportion problems)  Know what Type I and Type II errors are

 Test hypotheses for the difference between two independent population means (standard deviations known or unknown)  Test two means from related samples for the mean difference  Complete a Z test for the difference between two proportions  Use the F table to find critical F values  Complete an F test for the difference between two variances

 Recognize situations in which to use analysis of variance  Understand different analysis of variance designs  Perform a single-factor hypothesis test and interpret results  Conduct and interpret post-hoc multiple comparisons procedures  Analyze two-factor analysis of variance tests

Demand Management Qualitative Forecasting Methods Time Series Analysis – Static method – Adaptive method Simple & Weighted Moving Average Forecasts Exponential Smoothing Exponential Smoothing with trend Exponential Smoothing with trend & seasonality Simple Linear Regression

How to construct various control charts Which control charts to use for a particular type of data How to measure the capability of a process The basic themes of quality management and Deming’s 14 points The basic aspects of Six Sigma