一、拟合优度检验 二、方程的显著性检验(F检验) 三、变量的显著性检验（t检验） 四、参数的置信区间

一、模型的类型与变换 二、非线性回归实例

One CLRM assumption is: The model used in empirical analysis is \correctly specified\

11.1 The Nature of Heteroscedasticity Homoscedasticity: equal variance. Heteroscedasticity: unequal variance. Heteroscedasticity is usually found in cross-sectional data

Dummy variables (also indicator variables; binary variables categorical variables; dichotomous variables.) Qualitative variables in regression model For example: sex, race, color, religion, nationalit y, marital status, etc

Multiple Regression Model: A regression model with more than one explanatory variable, multiple because multiple nfluences (i.e., variables)affect the dependent variable

The Object of Hypothesis Testing To answer- How \good\ is the estimated regression line. How can we be sure that the estimated regression function (i.e., the SRF) is in fact a good estimator of the true PRF?

5.1 The Meaning of Regression Analysis 1.Regression analysisthe study of the relationship between one variable Y (the explained, or dependent variable) and one or more other variables X/Xs (explanatory, or independent variables)

Statistical inference draws conclusions about a population [i.e., probability density function(DF)] from random sample that has supposedly been drawn from that population

2.1 SOME NOTATION 1. The Summation Notation X, =X1++...+n can be abbreviated as:Σx,orΣx 2. Properties of the Summation Operator