Instruction 13 ANOVA Model 2 Is the Regression Analysis Where the Dependent Variable

question 31

Essay

Instruction 13.37
Given below are results from the regression analysis where the dependent variable is the number of weeks a worker is unemployed due to a layoff (Unemploy) and the independent variables are the age of the worker (Age), the number of years of education received (Edu), the number of years at the previous job (Job Yr), a dummy variable for marital status (Married: 1 = married, 0 = otherwise), a dummy variable for head of household (Head: 1 = yes, 0 = no) and a dummy variable for management position (Manager: 1 = yes, 0 = no). We shall call this Model 1.
Model 1
Regression Statistics
$\begin{array} { l l } \text { Multiple R } & 0.7035 \\ \text { R Square } & 0.4949 \\ \text { Adj. R Square } & 0.4030 \\ \text { Std. Error } & 18.4861 \\ \text { Observations } & 40 \end{array}$

ANOVA
$\begin{array} { l l l l l l l } & d f & \text { SS } & \text { MS } & F & \text { Signif F } & \\ \text { Regression } & 6 & 11048.6415 & 1841.4402 & 5.3885 & 0.00057 & \\ \text { Residual } & 33 & 11277.2586 & 341.7351 & & & \\ \text { Total } & 39 & 223325.9 & & & & \\ & & & & & & \\ & \text { Coeff } & \text { StdError } & \text { tStat } & p \text { value } & \text { Lower 95\% } & \text { Upper95\% } \\ \text { Intercept } & 32.6595 & 23.18302 & 1.4088 & 0.1683 & - 14.5067 & 79.8257 \\ \text { Age } & 1.2915 & 0.3599 & 3.5883 & 0.0011 & 0.5592 & 2.0238 \\ \text { Edu } & - 1.3537 & 1.1766 & - 1.1504 & 0.2582 & - 3.7476 & 1.0402 \\ \text { Job Yr } & 0.6171 & 0.5940 & 1.0389 & 0.3064 & - 0.5914 & 1.8257 \\ \text { Married } & - 5.2189 & 7.6068 & - 0.6861 & 0.4974 & - 20.6950 & 10.2571 \\ \text { Head } & - 14.2978 & 7.6479 & - 1.8695 & 0.0704 & - 29.8575 & 1.2618 \\ \text { Manager } & - 24.8203 & 11.6932 & - 2.1226 & 0.0414 & - 48.6102 & - 1.0303 \end{array}$ Model 2 is the regression analysis where the dependent variable is Unemploy and the independent variables are Age and Manager. The results of the regression analysis are given below:
Mode 2
Regression Statistics
$\begin{array} { l l } \text { Multiple R } & 0.6391 \\ \text { R Square } & 0.4085 \\ \text { Adj. R Square } & 0.3765 \\ \text { Std. Error } & 18.8929 \\ \text { Observations } & 40 \end{array}$

ANOVA
$\begin{array} { l l l l l l } & d f & \text { SS } & \text { MS } & F & \text { Signif F } \\ \text { Regression } & 2 & 9119.0897 & 4559.5448 & 12.7740 & 0.0000 \\ \text { Residual } & 37 & 13206.8103 & 356.9408 & & \\ \text { Total } & 39 & 22325.9 & & & \\ & & & & & \\ & \text { Coeff } & \text { StdError } & t \text { Stat } & p \text { value } & \\ \text { Intercept } & - 0.2143 & 11.5796 & - 0.0185 & 0.9853 & \\ \text { Age } & 1.4448 & 0.3160 & 4.5717 & 0.0000 & \\ \text { Manager } & - 22.5761 & 11.3488 & - 1.9893 & 0.0541 & \end{array}$
-Referring to Instruction 13.37 Model 1,what are the lower and upper limits of the 95% confidence interval estimate for the difference in the mean number of weeks a worker is unemployed due to a layoff between a worker who is married and one who is not after taking into consideration the effect of all the other independent variables?

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Definitions:

Financial Leverage

The use of borrowed money (debt) to amplify the potential returns from an investment.

EBIT-EPS Analysis

A tool used to determine the impact of different levels of debt on a company's earnings before interest and tax (EBIT) and earnings per share (EPS).

Leverage

The use of borrowed funds to finance the purchase of assets or increase the potential return of an investment.

Management Effectiveness

A measure of how well a company's management team utilizes resources to generate profits.