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Suppose the mean value E(y) of a response y is related to the quantitative independent variables x1and x2

E(y)=2+x1-3x2-x1x2

a) Identify and interpret the slope forx2

b) Plot the linear relationship between E(y) andx2for role="math" localid="1649796003444" x1=0,1,2, whererole="math" localid="1649796025582" 1x23

c) How would you interpret the estimated slopes?

d) Use the lines you plotted in part b to determine the changes in E(y) for eachrole="math" localid="1649796051071" x1=0,1,2.

e) Use your graph from part b to determine how much E(y) changes whenrole="math" localid="1649796075921" 3x15androle="math" localid="1649796084395" 1x23.

Short Answer

Expert verified

a) The slope of x2from the equation can be seen is -3. A negative value indicates that x2has an inverse relation with y and a higher value denotes that its of high magnitude.

b) Graph

c) For every change in the value of x1out slope of the line changes and the line becomes steeper.

d) For the given value of x2between 1x23, the changes in the value of x1makes the slope of the line becomes steeper as the slope parameter increases from 3 to 4 to 5 for the values of x1 as 0, 1, and 2.

e) E(y) changes by 1 to 17 to units when the value of x2is 1x23and x1 is3x15

Step by step solution

01

Slope of x2

The slope ofx2from the equation that can be seen is -3. A negative value indicates thatx2 has an inverse relation with y and a higher value denotes that its of high magnitude.

02

Graph

Given

Ey=2+x1-3x2-x1x2forx1=0=2+0-3x2-0×x2=2-3x2

Now to plot this equation, make a table

Y

-1

-7

X2

1

3

Given

Ey=2+x1-3x2-x1x2forx1=1=2+1-3x2-1×x2=3-4x2

Now to plot this equation, make a table

Y

-1

-9

X2

1

3

Given

Ey=2+x1-3x2-x1x2forx1=2=2+2-3x2-2×x2=4-5x2

Now to plot this equation, make a table

Y

-1

-11

X2

1

3

03

Interpretation of graph

As it can be seen in the graph, for the value ofx1=0,1,2 , E(y) passes through (1, -1) whenx2 is. 1x23And for every change in the value ofx1out slope of the line changes and the line becomes steeper.

04

Explanation of the slope

For the given value of x2between 1x23, the changes in the value of x1makes the slope of the line becomes steeper as the slope parameter increases from 3 to 4 to 5 for the values of x1as 0, 1, and 2.

05

Changes in E(y)

E(y) changes by 1 to 17 to units when the value of x2is 1x23and x1is 3x15

Given,

role="math" localid="1649798013525" Ey=2+x1-3x2-x1x2forx1=3andx2=1y=2+3-3×1-3×1y=-1

Given,

Ey=2+x1-3x2-x1x2forx1=5andx2=3y=2+5-3×3-5×3y=-17

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Most popular questions from this chapter

Suppose you fit the quadratic model E(y)=β0+β1x+β2x2to a set of n = 20 data points and found R2=0.91, SSyy=29.94, and SSE = 2.63.

a. Is there sufficient evidence to indicate that the model contributes information for predicting y? Test using a = .05.

b. What null and alternative hypotheses would you test to determine whether upward curvature exists?

c. What null and alternative hypotheses would you test to determine whether downward curvature exists?

Minitab was used to fit the complete second-order modeE(y)=β0+β1x1+β2x2+β3x1x2+β4x12+β5x22to n = 39 data points. The printout is shown on the next page.

a. Is there sufficient evidence to indicate that at least one of the parameters—β1,β2,β3,β4, andβ1,β2,β3,β4—is nonzero? Test usingα=0.05.

b. TestH0:β4=0againstHa:β40. Useα=0.01.

c. TestH0:β5=0againstHa:β50. Useα=0.01.

d. Use graphs to explain the consequences of the tests in parts b and c.

Question: Orange juice demand study. A chilled orange juice warehousing operation in New York City was experiencing too many out-of-stock situations with its 96-ounce containers. To better understand current and future demand for this product, the company examined the last 40 days of sales, which are shown in the table below. One of the company’s objectives is to model demand, y, as a function of sale day, x (where x = 1, 2, 3, c, 40).

  1. Construct a scatterplot for these data.
  2. Does it appear that a second-order model might better explain the variation in demand than a first-order model? Explain.
  3. Fit a first-order model to these data.
  4. Fit a second-order model to these data.
  5. Compare the results in parts c and d and decide which model better explains variation in demand. Justify your choice.

Question: Consider the model:

y=β0+β1x1+β2x2+β3x3+ε

where x1 is a quantitative variable and x2 and x3 are dummy variables describing a qualitative variable at three levels using the coding scheme

role="math" localid="1649846492724" x2=1iflevel20otherwisex3=1iflevel30otherwise

The resulting least squares prediction equation is y^=44.8+2.2x1+9.4x2+15.6x3

a. What is the response line (equation) for E(y) when x2 = x3 = 0? When x2 = 1 and x3 = 0? When x2 = 0 and x3 = 1?

b. What is the least squares prediction equation associated with level 1? Level 2? Level 3? Plot these on the same graph.

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