TABLE 13-11 A Weight-Loss Clinic Wants to Use Regression Analysis to Build

question 97

Multiple Choice

TABLE 13-11
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:
Y = Weight loss (in pounds)
X1 = Length of time in weight-loss program (in months)
X2 = 1 if morning session, 0 if not
X3 = 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 = β0 + β1X1 + β2X2 + β3X3 + β4X1X2 + β5X1X3 + ε
Partial output from Microsoft Excel follows:

-Referring to Table 13-11, which of the following statements is supported by the analysis shown?

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

Identify appropriate bootstrapping methods based on the characteristics of the original sample and the bootstrap distribution.

Differentiate between bootstrap and permutation resampling methods.

Recognize the limitations and accuracies of bootstrap confidence intervals with small samples.

Understand the application of different bootstrap confidence interval methods (e.g., percentile, BCa) depending on the bias and sample size.

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