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Instruction 13-9
a Weight-Loss Clinic Wants to Use Regression Analysis

question 246

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Instruction 13-9
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)
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:
Regression Statistics
 Multiple R 0.73514 R Square 0.540438 Adjusted R Square 0.157469 Standard Error 12.4147 Observations 12\begin{array} { l l } \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}
ANOVA
F=5.41118 Significance F=0.040201 Intercept  Coeff  StdError t Stat P-value  Length (X1) 0.08974414.1270.00600.9951 Morn Ses (X2) 6.225382.434732.549560.0479 Aft Ses (X3) 2.21727222.14160.1001410.9235 Length*Morn Ses 11.82333.15453.5589010.0165 Length*Aft Ses 0.770583.5620.2163340.83590.541473.359880.1611580.8773\begin{array} { c c c c c } F = 5.41118 & \text { Significance } F = 0.040201 & & \\ & & & & \\ \text { Intercept } & \text { Coeff } & \text { StdError } & t \text { Stat } & P \text {-value } \\ \text { Length } \left( X _ { 1 } \right) & 0.089744 & 14.127 & 0.0060 & 0.9951 \\ \text { Morn Ses } \left( X _ { 2 } \right) & 6.22538 & 2.43473 & 2.54956 & 0.0479 \\ \text { Aft Ses } \left( X _ { 3 } \right) & 2.217272 & 22.1416 & 0.100141 & 0.9235 \\ \text { Length*Morn Ses } & 11.8233 & 3.1545 & 3.558901 & 0.0165 \\ \text { Length*Aft Ses } & 0.77058 & 3.562 & 0.216334 & 0.8359 \\ & - 0.54147 & 3.35988 & - 0.161158 & 0.8773 \end{array}
-Referring to Instruction 13-9,in terms of the ?'s in the model,give the mean change in weight-loss (Y) for every 1 month increase in time in the program (X1) when attending the morning session.

Determine the book value of fixed assets and analyze changes over time.
Understand the concept and methods of depreciation, amortization, and depletion.
Journalize entries for the acquisition, depreciation, amortization, and disposal of assets.
Calculate the gain or loss on the sale or disposal of assets.

Definitions:

Long-Run Supply Curve

As it applies to macroeconomics, a supply curve for which price, but not real output, changes when the demand curves shifts; a vertical supply curve that implies fully flexible prices.

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Pure Competition

A market structure characterized by a large number of buyers and sellers dealing in perfectly substitutable goods or services.

Market Entry

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