Instruction 13-16
Given Below Are Results from the Regression Analysis

question 101

True/False

Instruction 13-16
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.
$$\begin{array} { l r } \hline { \text { Regression Statistics } } \\\hline \text { Multiple R } & 0.7035 \\\text { R Square } & 0.4949 \\\text { Adjusted R } & 0.4030 \\\text { Square } & \\\text { Standard } & 18.4861 \\\text { Error } \\\text { Observations } & 40 \\\hline\end{array}$$ ANOVA
$\begin{array}{lrrrrr}& \text { df } &{\text { SS }} & \text { MS } & F&\text { Significance F } \\\hline \text { Regression } & 6 & 11048.6415 & 1841.4402 & 5.3885 & 0.00057 \\\text { Residual } & 33 & 11277.2586 & 341.7351 & & \\\text { Total } & 39 & 22325.9 & &\end{array}$

$\begin{array}{lrrrrrr} & \text { Coefficients } & \text { Standard Error } & t \text { Stat } & \text { P-value } & \text { Lower 95\% } & \text { Upper 95\% } \\\hline \text { Intercept } & 32.6595 & 23.18302 & 1.4088 & 0.1683 & -14.5067 & 79.8257 \\\text { Age } & 1.2915 & 0.3599 & 3.5883 & 0.0011 & 0.5592 & 2.0238 \\\text { Edu } & -1.3537 & 1.1766 & -1.1504 & 0.2582 & -3.7476 & 1.0402 \\\text { Job Yr } & 0.6171 & 0.5940 & 1.0389 & 0.3064 & -0.5914 & 1.8257 \\\text { Married } & -5.2189 & 7.6068 & -0.6861 & 0.4974 & -20.6950 & 10.2571 \\\text { Head } & -14.2978 & 7.6479 & -1.8695 & 0.0704 & -29.8575 & 1.2618 \\\text { Manager } & -24.8203 & 11.6932 & -2.1226 & 0.0414 & -48.6102 & -1.0303\end{array}$ 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:
$$\begin{array} { l r } \hline { \text { Regression Statistics } } \\\hline \text { Multiple R } & 0.6391 \\\text { R Square } & 0.4085 \\\text { Adjusted R } & 0.3765 \\\text { Square } & \\\text { Standard Error } & 18.8929 \\\text { Observations } & 40\\\hline\end{array}$$ $$\begin{array}{l}\text { ANOVA }\\\begin{array} { l r r r l r } \hline & d f & { S S } & { M S } & F & \text { Significance } F \\\hline \text { Regression } & 2 & 9119.0897 & 4559.5448 & 12.7740 & 0.0000 \\\text { Residual } & 37 & 13206.8103 & 356.9408 & & \\\text { Total } & 39 & 22325.9 & & & \\\hline\end{array}\\\begin{array} { l r r r r } \hline & \text { Coefficients } & \text { Standard Error } & { t \text { Stat } } & P \text {-value } \\\hline \text { Intercept } & - 0.2143 & 11.5796 & - 0.0185 & 0.9853 \\\text { Age } & 1.4448 & 0.3160 & 4.5717 & 0.0000 \\\text { Manager } & - 22.5761 & 11.3488 & - 1.9893 & 0.0541 \\\hline\end{array}\end{array}$$
-Referring to Instruction 13-16 Model 1,you can conclude that,holding constant the effect of the other independent variables,the number of years of education received has no impact on the mean number of weeks a worker is unemployed due to a layoff at a 1% level of significance if all you have is the information of the 95% confidence interval estimate for ?₂.

Recognize the implications of job design and ergonomic considerations on employee performance and satisfaction.

Understand the process and components of work flow design and analysis.

Analyze the role of human resource management in defining and structuring jobs within organizations.

Evaluate the impact of job enrichment, extension, and rotation on job satisfaction and organizational productivity.

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Definitions:

Minimum Cash Balance

The smallest amount of cash that a company seeks to maintain in its accounts to ensure financial stability and operational efficiency.

Accounts Receivable Balance

The total amount of money owed to a company by its customers for goods or services provided on credit, yet to be paid.

Accounts Receivable Period

The average number of days it takes for a business to collect payments owed by its customers.

Credit Sales

Sales made by a business for which payment is received at a later date, extending credit to the buyer.