Instruction 16-6
Given Below Are Results from the Regression Analysis

question 62

True/False

Instruction 16-6
Given below are results from the regression analysis on 40 observations where the dependent variable is the number of weeks a worker is unemployed due to a layoff (Y) and the independent variables are the age of the worker (X₁), the number of years of education received (X₂), the number of years at the previous job (X₃), a dummy variable for marital status (X₄: 1 = married, 0 = otherwise), a dummy variable for head of household (X₅: 1 = yes, 0 = no) and a dummy variable for management position (X₆: 1 = yes, 0 = no).
The coefficient of multiple determination (R²_j) the regression model using each of the 6 variables X_j as the dependent variable and all other X variables as independent variables are, respectively, 0.2628, 0.1240, 0.2404, 0.3510, 0.3342 and 0.0993.
The partial results from best-subset regression are given below:
$$\begin{array} { | l | l | l | l | } \hline \text { Model } & \text { R Square } & \text { Adj. R Square } & \text { Std. Error } \\\hline X _ { 1 } X _ { 5 } X _ { 6 } & 0.4568 & 0.4116 & 18.3534 \\\hline X _ { 1 } X _ { 2 } X _ { 5 } X _ { 6 } & 0.4697 & 0.4091 & 18.3919 \\\hline X _ { 1 } X _ { 3 } X _ { 5 } X _ { 6 } & 0.4691 & 0.4084 & 18.4023 \\\hline X _ { 1 } X _ { 2 } X _ { 3 } X _ { 5 } X _ { 6 } & 0.4877 & 0.4123 & 18.3416 \\\hline X _ { 1 } X _ { 2 } X _ { 3 } X _ { 4 } X _ { 5 } X _ { 6 } & 0.4949 & 0.4030 & 18.4861 \\\hline\end{array}$$
-Referring to Instruction 16-6,the model that includes X₁,X₂,X₃,X₅ and X₆ should be among the appropriate models using the Mallow's C_p statistic.

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Definitions:

Cases

Instances or occurrences of a particular condition or category being studied in research or documented in various fields such as law or medicine.

Arithmetic Operations

Basic mathematical computations including addition, subtraction, multiplication, and division.

Categorical

Pertaining to data that can be divided into specific groups or categories that are qualitatively distinct.

Categorical Variables

Variables that represent categories with qualitative characteristics, such as gender, race, or yes/no responses, and do not inherently carry a numerical value.