Instruction 13 $Y =$ Weight-Loss (In Kilograms) $X _ { 1 } =$

Instruction 13.38
A weight-loss clinic wants to use regression analysis to build a model for weight-loss of a client (measured in kilograms) . Two variables thought to effect weight-loss are client's length of time on the weight loss program and time of session. These variables are described below:
$Y =$ Weight-loss (in kilograms)
$X _ { 1 } =$ Length of time in weight-loss program (in months)
$x _ { 2 } = 1$ if morning session, 0 if not
$x _ { 3 } = 1$ if afternoon session, 0 if not (Base level = evening session)
Data for 12 clients on a weight-loss program at the clinic were collected and used to fit the interaction model:
$$Y = \beta 0 + \beta _ { 1 } X _ { 1 } + \beta _ { 2 } X _ { 2 } + \beta _ { 3 } X _ { 3 } + \beta _ { 4 } X _ { 1 } X _ { 2 } + \beta _ { 5 } X _ { 1 } X _ { 3 } + \varepsilon$$
Partial output from Microsoft Excel follows:

-Referring to Instruction 13.38,which of the following statements is supported by the analysis shown?

A) There is sufficient evidence (at ? = 0.05) of curvature in the relationship between weight-loss (Y) and months in program (X₁) .
B) There is sufficient evidence (at ? = 0.10) to indicate that the session time (morning, afternoon, evening) affects weight-loss (Y) .
C) There is sufficient evidence (at ? = 0.05) to indicate that the relationship between weight-loss (Y) and months in program (X₁) depends on session time.
D) There is insufficient evidence (at ? = 0.10) to indicate that the relationship between weight-loss (Y) and months in program (X₁) depends on session time.