Springer Texts in Business and Economics

# Dependent Variable: LNC

Analysis of Variance

 Sum of Mean Source DF Squares Square F Value Prob > F Model 1 0.04693 0.04693 1.288 0.2625 Error 44 1.60260 0.03642 C Total 45 1.64953 Root MSE 0.19085 R-square 0.0285 Dep Mean 4.84784 Adj R-sq 0.0064 C. V. 3.93675
 Parameter Estimates

INTERCEP 1 5.931889 0.95542530

LNY 1 -0.227003 0.19998321

The income elasticity is —0.227 which is negative! Its standard error is (0.1999) and the t-statistic fortesting this income elasticity is zero is —1.135 which is insignificant with a p-value of 0.26. Hence, we cannot reject the null hypothesis. R2 = 0.0285 and s = 0.19085. This regression is not very useful. The income variable is not significant and the R2 indicates that the

regression explains only 2.8% of the variation in consumption. b. Plot of Residuals, and the 95% confidence interval for the predicted value.

SAS Program for 3.14 Data CIGARETT;

Input OBS STATE \$ LNC LNP LNY;

Cards;

Proc reg data=cigarett;
model lnc=lny;

*plot residual. *lny=’*’;

*plot (U95. L95.)*lny=’-’ p.*lny/overlay symbol=‘*’;

output out=out1 r=resid p=pred u95=upper95 195=lower95;

proc plot data=out1 vpercent=75 hpercent=100; plot resid*lny=‘*’;

proc plot data=out1 vpercent=95 hpercent=100; plot (Upper95 Lower95)*lny=‘-’ Pred*lny=‘*’

/overlay;

run;

Добавить комментарий

## Springer Texts in Business and Economics

### The General Linear Model: The Basics

7.1 Invariance of the fitted values and residuals to non-singular transformations of the independent variables. The regression model in (7.1) can be written as y = XCC-1" + u where …

### Regression Diagnostics and Specification Tests

8.1 Since H = PX is idempotent, it is positive semi-definite with b0H b > 0 for any arbitrary vector b. Specifically, for b0 = (1,0,.., 0/ we get hn …

### Generalized Least Squares

9.1 GLS Is More Efficient than OLS. a. Equation (7.5) of Chap. 7 gives "ois = " + (X'X)-1X'u so that E("ois) = " as long as X and u …

## Как с нами связаться:

Украина:
г.Александрия
тел./факс +38 05235  77193 Бухгалтерия
+38 050 512 11 94 — гл. инженер-менеджер (продажи всего оборудования)

+38 050 457 13 30 — Рашид - продажи новинок
e-mail: msd@msd.com.ua
Схема проезда к производственному офису:
Схема проезда к МСД

Партнеры МСД

## Контакты для заказов шлакоблочного оборудования:

+38 096 992 9559 Инна (вайбер, вацап, телеграм)
Эл. почта: inna@msd.com.ua