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Question: Glass as a waste encapsulant. Because glass is not subject to radiation damage, encapsulation of waste in glass is considered to be one of the most promising solutions to the problem of low-level nuclear waste in the environment. However, chemical reactions may weaken the glass. This concern led to a study undertaken jointly by the Department of Materials Science and Engineering at the University of Florida and the U.S. Department of Energy to assess the utility of glass as a waste encapsulant. Corrosive chemical solutions (called corrosion baths) were prepared and applied directly to glass samples containing one of three types of waste (TDS-3A, FE, and AL); the chemical reactions were observed over time. A few of the key variables measured were

y = Amount of silicon (in parts per million) found in solution at end of experiment. (This is both a measure of the degree of breakdown in the glass and a proxy for the amount of radioactive species released into the environment.)

x1 = Temperature (°C) of the corrosion bath

x2 = 1 if waste type TDS-3A, 0 if not

x3 = 1 if waste type FE, 0 if not

(Waste type AL is the base level.) Suppose we want to model amount y of silicon as a function of temperature (x1) and type of waste (x2, x3).

a. Write a model that proposes parallel straight-line relationships between amount of silicon and temperature, one line for each of the three waste types.

b. Add terms for the interaction between temperature and waste type to the model of part a.

c. Refer to the model of part b. For each waste type, give the slope of the line relating amount of silicon to temperature.

e. Explain how you could test for the presence of temperature–waste type interaction.

Short Answer

Expert verified

Answer

a. A model that proposes parallel straight-line relationships between amount of silicon and temperature can be written asy=β0+β1x1+β2x2+β3x3.

b. A model that proposes relationships between amount of silicon and temperature and waste types with interaction between temperature and waste types can be written as y=β0+β1x1+β2x2+β3x3+β4x1x2+β5x1x3.

c. For AL waste type, the slope of the line will be β1. For TSA-3A waste type, the slope of the line will be localid="1651563388536" (β1+β4).For FE waste type, the slope of the line will be(β1+β5)..

d. The presence of temperature-waste type interaction can be tested by doing hypothesis testing on β parameters indicating interaction terms.

Step by step solution

01

Model 

A model that proposes parallel straight-line relationships between amount of silicon and temperature can be indicated by a model where there is no interaction amongst the variables in the model.

Mathematically, it can be written as y=β0+β1x1+β2x2+β3x3.

02

Interaction model

A model that proposes relationships between amount of silicon and temperature and waste types with interaction between temperature and waste types can be written asy=β0+β1x1+β2x2+β3x3+β4x1x2+β5x1x3.

03

Slope of the line for each waste type

For the three waste types; TDS-3A, FE, and AL, two variables are introduced in the model x2 for TSA-3A and x3 for FE. Therefore, Al indicates the base levels.

For AL waste type, the slope of the line will be

y=β0+β1x1+β2x2+β3x3+β4x1x2+β5x1x3y=β0+β1x1+β2(0)+β3(0)+β4x1(0)+β5(0)y=β0+β1x1

The slope of the line is β1.

For TSA-3A waste type, the slope of the line will be

role="math" localid="1651554382496" y=β0+β1x1+β2x2+β3x3+β4x1x2+β5x1x3y=β0+β1x1+β2(1)+β3(0)+β4x1(0)+β5x1(0)forx2=1,andx3=0y=(β0+β2)+(β1+β4)x1

Theslopeofthelineis(β1+β4).

For FE waste type, the slope of the line will be

y=β0+β1x1+β2x2+β3x3+β4x1x2+β5x1x3y=β0+β1x1+β2(1)+β3(0)+β4x1(0)+β5x1(1)forx2=0,andx3=1y=(β0+β3)+(β1+β5)x1

Theslopeofthelineis(β1+β5).

04

Hypotheses testing

The presence of temperature-waste type interaction can be tested by doing hypothesis testing on β parameters indicating interaction terms.

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Most popular questions from this chapter

Suppose you used Minitab to fit the model y=β0+β1x1+β2x2+ε

to n = 15 data points and obtained the printout shown below.

  1. What is the least squares prediction equation?

  2. Find R2and interpret its value.

  3. Is there sufficient evidence to indicate that the model is useful for predicting y? Conduct an F-test using α = .05.

  4. Test the null hypothesis H0: β1= 0 against the alternative hypothesis Ha: β1≠ 0. Test using α = .05. Draw the appropriate conclusions.

  5. Find the standard deviation of the regression model and interpret it.

Suppose you fit the model y =β0+β1x1+β1x22+β3x2+β4x1x2+εto n = 25 data points with the following results:

β^0=1.26,β^1= -2.43,β^2=0.05,β^3=0.62,β^4=1.81sβ^1=1.21,sβ^2=0.16,sβ^3=0.26, sβ^4=1.49SSE=0.41 and R2=0.83

  1. Is there sufficient evidence to conclude that at least one of the parameters b1, b2, b3, or b4 is nonzero? Test using a = .05.

  2. Test H0: β1 = 0 against Ha: β1 < 0. Use α = .05.

  3. Test H0: β2 = 0 against Ha: β2 > 0. Use α = .05.

  4. Test H0: β3 = 0 against Ha: β3 ≠ 0. Use α = .05.

When a multiple regression model is used for estimating the mean of the dependent variable and for predicting a new value of y, which will be narrower—the confidence interval for the mean or the prediction interval for the new y-value? Why?

Question: Reality TV and cosmetic surgery. Refer to the Body Image: An International Journal of Research (March 2010) study of the impact of reality TV shows on one’s desire to undergo cosmetic surgery, Exercise 12.17 (p. 725). Recall that psychologists used multiple regression to model desire to have cosmetic surgery (y) as a function of gender(x1) , self-esteem(x2) , body satisfaction(x3) , and impression of reality TV (x4). The SPSS printout below shows a confidence interval for E(y) for each of the first five students in the study.

  1. Interpret the confidence interval for E(y) for student 1.
  2. Interpret the confidence interval for E(y) for student 4

Question: Personality traits and job performance. Refer to the Journal of Applied Psychology (Jan. 2011) study of the relationship between task performance and conscientiousness, Exercise 12.54 (p. 747). Recall that the researchers used a quadratic model to relate y = task performance score (measured on a 30-point scale) to x1 = conscientiousness score (measured on a scale of -3 to +3). In addition, the researchers included job complexity in the model, where x2 = {1 if highly complex job, 0 if not}. The complete model took the form

E(y)=β0+β1x1+β2x12+β3x2+β4x1x2+β5x12x2herex2=1E(y)=β0+β1x1+β2x12+β3(1)+β4x1(1)+β5(1)2(1)E(y)=(β0+β3)+(β1+β4)x1+(β2+β5)(x1)2

a. For jobs that are not highly complex, write the equation of the model for E1y2 as a function of x1. (Substitute x2 = 0 into the equation.)

b. Refer to part a. What do each of the b’s represent in the model?

c. For highly complex jobs, write the equation of the model for E(y) as a function of x1. (Substitute x2 = 1 into the equation.)

d. Refer to part c. What do each of the b’s represent in the model?

e. Does the model support the researchers’ theory that the curvilinear relationship between task performance score (y) and conscientiousness score (x1) depends on job complexity (x2)? Explain.

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