管理经济学,英文版.ppt

1、Chapter 4,Basic Estimation Techniques,4-2,Simple Linear Regression,Simple linear regression model relates dependent variable Y to one independent (or explanatory) variable X,Slope parameter (b) gives the change in Y associated with a one-unit change in X,4-3,Method of Least Squares,The sample regres

2、sion line is an estimate of the true regression line,4-4,Sample Regression Line (Figure 4.2),A,0,8,000,2,000,10,000,4,000,6,000,10,000,20,000,30,000,40,000,50,000,60,000,70,000,Advertising expenditures (dollars),Sales (dollars),S,4-5,The distribution of values the estimates might take is centered ar

3、ound the true value of the parameter An estimator is unbiased if its average value (or expected value) is equal to the true value of the parameter,Unbiased Estimators,4-6,Relative Frequency Distribution* (Figure 4.3),0,8,2,10,4,6,1,1,3,5,7,9,*Also called a probability density function (pdf),4-7,Must

4、 determine if there is sufficient statistical evidence to indicate that Y is truly related to X (i.e., b 0),Statistical Significance,Test for statistical significance using t-tests or p-values,4-8,First determine the level of significance Probability of finding a parameter estimate to be statistical

5、ly different from zero when, in fact, it is zero Probability of a Type I Error 1 level of significance = level of confidence,Performing a t-Test,4-9,Performing a t-Test,Use t-table to choose critical t-value with n k degrees of freedom for the chosen level of significance n = number of observations

6、k = number of parameters estimated,4-10,Performing a t-Test,If absolute value of t-ratio is greater than the critical t, the parameter estimate is statistically significant,4-11,Using p-Values,Treat as statistically significant only those parameter estimates with p-values smaller than the maximum ac

7、ceptable significance level p-value gives exact level of significance Also the probability of finding significance when none exists,4-12,Coefficient of Determination,R2 measures the percentage of total variation in the dependent variable that is explained by the regression equation Ranges from 0 to

8、1 High R2 indicates Y and X are highly correlated,4-13,F-Test,Used to test for significance of overall regression equation Compare F-statistic to critical F-value from F-table Two degrees of freedom, n k & k 1 Level of significance If F-statistic exceeds the critical F, the regression equation overall is statistically significant,4-14,Multiple Regression,Uses more than one explanatory variable Coefficient for each explanatory variable measures the change in the dependent variable associated with a one-unit ch