SCENARIO 17-6
a Weight-Loss Clinic Wants to Use Regression Analysis

question 332

True/False

SCENARIO 17-6
A weight-loss clinic wants to use regression analysis to build a model for weight-loss of a client
(measured in pounds). Two variables thought to affect weight-loss are client's length of time on the
weight loss program and time of session. These variables are described below: $\begin{aligned} Y & = \text { Weight-loss (in pounds) } \\ X _ { 1 } & = \text { Length of time in weight-loss program (in months) } \\ X _ { 2 } & = 1 \text { if morning session, } 0 \text { if not } \\ X _ { 3 } & = 1 \text { if afternoon session, } 0 \text { if not } \quad \text { (Base level = evening session) } \end{aligned}$
Data for 12 clients on a weight-loss program at the clinic were collected and used to fit the interaction model: $\quad Y = \beta _ { 0 } + \beta _ { 1 } X _ { 1 } + \beta _ { 2 } X _ { 2 } + \beta _ { 3 } X _ { 3 } + \beta _ { 4 } X _ { 1 } X _ { 2 } + \beta _ { 5 } X _ { 1 } X _ { 3 } + \varepsilon$

Partial output from Microsoft Excel follows:

$\begin{array}{ll}{\text { Regression Statistics }} \\\text { Multiple R } & 0.73514 \\\text { R Square } & 0.540438 \\\text { Adjusted R Square } & 0.157469 \\\text { Standard Error } & 12.4147 \\\text { Observations } & 12\end{array}$

$\text { ANOVA }$
$F=5.41118 \quad \text { Significance } F=0.040201$

$\begin{array}{ccccc} & \text { Coeff } & \text { StdError } & t \text { Stat } & P \text {-value } \\\text { Intercept } & 0.089744 & 14.127 & 0.0060 & 0.9951 \\\text { Length }\left(X_{1}\right) & 6.22538 & 2.43473 & 2.54956 & 0.0479 \\\text { Morn Ses }\left(X_{2}\right) & 2.217272 & 22.1416 & 0.100141 & 0.9235 \\\text { Aft Ses }\left(X_{3}\right) & 11.8233 & 3.1545 & 3.558901 & 0.0165 \\\text { Length*Morn Ses } & 0.77058 & 3.562 & 0.216334 & 0.8359 \\\text { Length"Aft Ses } & -0.54147 & 3.35988 & -0.161158 & 0.8773\end{array}$


-Referring to Scenario 17-6, the overall model for predicting weight-loss (Y) is
statistically significant at the 0.05 level.

Identify and explain the process and importance of disaggregation in planning.

Comprehend how yield management strategies apply to business scenarios with specific cost structures.

Analyze how demand fluctuation impacts aggregate planning and the applicability of different strategies.

Understand the role of human resources and demand management in service sector aggregate planning.

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Definitions:

Assigns Jobs

The act of allocating or designating work tasks to individuals or groups based on criteria such as skills, availability, or strategic importance.

Work Centres

Specific locations, machines, or groups of machines within a manufacturing facility where distinct types of processes are performed.

Assignment Method

The assignment method is a mathematical technique used for allocating resources or tasks to units in an efficient manner, often used in operations research.

Job-Machine Combination

A matching process in operations management that involves assigning specific jobs to specific machines or workstations, optimizing for efficiency and output.