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

question 34

Multiple Choice

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,which of the following is the correct null hypothesis to determine whether there is a significant relationship between the number of weeks a worker is unemployed due to a layoff and the entire set of explanatory variables?

• A) H 0 : \(\beta\) 0 = \(\beta\) 1 = \(\beta\) 2 = \(\beta\) 3 = \(\beta\) 4 = \(\beta\) 5 = \(\beta\) 6 = 0
• B) H 0 : \(\beta\) 1 = \(\beta\) 2 = \(\beta\) 3 = \(\beta\) 4 = \(\beta\) 5 = \(\beta\) 6
• C) H 0 : \(\beta\) 1 = \(\beta\) 2 = \(\beta\) 3 = \(\beta\) 4 = \(\beta\) 5 = \(\beta\) 6 = 0
• D) H 0 : \(\beta\) 0 = \(\beta\) 1 = \(\beta\) 2 = \(\beta\) 3 =\(\beta\) 4 = \(\beta\) 5 = \(\beta\) 6

---

Definitions:

External Factors

Elements outside of an individual or system that can influence or affect outcomes, behaviors, or processes.

Instrument

An instrument in the medical context typically refers to a tool or device designed for specific diagnostic or therapeutic tasks during treatment or surgery.

Financial Record

Documentation that tracks the income, expenses, and other financial activities of an individual or organization.

Patient Registration Form

A document used in healthcare settings for collecting essential information about a new or returning patient, including demographic and insurance data.