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

question 4

Short Answer

Instruction 13.25
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
$\begin{array} { l l l l l l l } & d f & \text { SS } & \text { MS } & F & \text { Signiff } & \\ \text { Regression } & 6 & 11048.6415 & 1841.4402 & 5.3885 & 0.00057 & \\ \text { Residual } & 33 & 11277.2586 & 341.7351 & & & \\ \text { Total } & 39 & 223325.9 & & & & \\ & & & & & & \\ & \text { Coeff } & \text { StdError } & \text { tStat } & p \text { value } & \text { Lower 95\% } & \text { Upper95\% } \\ \text { Intercept } & 32.6595 & 23.18302 & 1.4088 & 0.1683 & - 14.5067 & 79.8257 \\ \text { Age } & 1.2915 & 0.3599 & 3.5883 & 0.0011 & 0.5592 & 2.0238 \\ \text { Edu } & - 1.3537 & 1.1766 & - 1.1504 & 0.2582 & - 3.7476 & 1.0402 \\ \text { Job Yr } & 0.6171 & 0.5940 & 1.0389 & 0.3064 & - 0.5914 & 1.8257 \\ \text { Married } & - 5.2189 & 7.6068 & - 0.6861 & 0.4974 & - 20.6950 & 10.2571 \\ \text { Head } & - 14.2978 & 7.6479 & - 1.8695 & 0.0704 & - 29.8575 & 1.2618 \\ \text { Manager } & - 24.8203 & 11.6932 & - 2.1226 & 0.0414 & - 48.6102 & - 1.0303 \end{array}$ 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
$\begin{array} { l l l l l l } & d f & \text { SS } & \text { MS } & F & \text { Signiff } \\ \text { Regression } & 2 & 9119.0897 & 4559.5448 & 12.7740 & 0.0000 \\ \text { Residual } & 37 & 13206.8103 & 356.9408 & & \\ \text { Total } & 39 & 22325.9 & & & \\ & & & & & \\ & \text { Coeff } & \text { StdError } & t \text { Stat } & p \text { value } & \\ \text { Intercept } & - 0.2143 & 11.5796 & - 0.0185 & 0.9853 & \\ \text { Age } & 1.4448 & 0.3160 & 4.5717 & 0.0000 & \\ \text { Manager } & - 22.5761 & 11.3488 & - 1.9893 & 0.0541 & \end{array}$
-Referring to Instruction 13.25 Model 1,what is the standard error of estimate?

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Definitions:

Animals

Multicellular, eukaryotic organisms in the kingdom Animalia that are characterized by their ability to move voluntarily, consume organic materials, and have sensory and nervous systems.

Lophotrochozoa

A clade within the animal kingdom that includes organisms with a distinctive developmental stage or feeding structure, such as mollusks, annelids, and brachiopods.

Deuterostomes

A major group of animals characterized by their embryonic development, in which the anus forms before the mouth during early embryogenesis.

Embryos

Early developmental stages of multicellular organisms following fertilization, during which cells divide and specialize to form the structure and organs of the organism.