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A experiment using a single replicate of a 2 4 factorial design. After analyzing the data, the following results are available: Model Term Effect Estimate

  1. A experiment using a single replicate of a 24 factorial design. After analyzing the data, the following results are available:

Model Term

Effect Estimate

Sum of Squares

% Contribution

Intercept

X

X

X

A-A

-9.75

380.25

40.4952

B-B

-0.25

0.0266241

C-C

-0.25

0.25

0.0266241

D-D

90.25

9.61129

AB

4.5

81

AC

0.5

1

0.106496

AD

-3.5

49

5.21832

BC

-1

4

0.425985

BD

-2

16

1.70394

CD

1

4

0.425985

ABC

-6.25

156.25

16.64

ABD

4.75

90.25

9.61129

ACD

-0.25

0.25

0.0266241

BCD

-2.75

30.25

3.22151

ABCD

3

3.83387

The grand average of all 16 observations is 83.75 and the total sum of squares is 939.00.

Answer the following questions.

  1. Fill in the 4 blanks in the table above,

  1. Is this an I-optimal design (circle the correct answer)? Yes

  1. A experimenter also ran 4 center points (the response data is not included in the calculations above) and observed the following results: 88 89, 92, and 87. The mean square for pure error is

  1. 2.00
  2. 3.85
  3. 4.67
  4. 5.25
  5. None of the above

  1. The value of the F-statistic for pure quadratic curvature is
    1. 10.51
    2. 9.98
    3. 8.75
    4. 9.50
    5. None of the above

  1. The table below shows the coded and natural (engineering) units for the factors. Find the regression model(s) for predicting the response in terms of the natural units assuming that the model contains only the main effects of A and D and the AD interaction.

Factor

Natural levels

Coded levels (x’s)

A – time

80, 120 (minutes)

-1, 1

B - temperature

150, 200

(deg C)

-1, 1

C - pressure

(100, 150) psi

-1, 1

D - catalyst type

Organic, inorganic

-1, 1

  1. Consider the 22 factorial design shown
  2. 6.8. A bacteriologist is interested in the effects of two dif- ferent culture media and two different times
    1. Write the design matrix in coded units and the appropriate response totals in the table below.

Run

Response

1

2

3

4

  1. What is the estimate of the AB interaction effect?

  1. What is the model regression coefficient for the AB interaction effect? ­­­­­­­­­­­­­­­­__________________

  1. In the full model ANOVA how many degrees of freedom are available for pure error?


6.8. A bacteriologist is interested in the effects of two dif- ferent culture media and two different times on the growth of a particular virus. He or she performs six replicates of a 2 design, making the runs in random order. Analyze the bacte- rial growth data that follow and draw appropriate conclu- sions. Analyze the residuals and comment on the model's adequacy. Time (h) 12 18 21 23 20 37 38 35 1 Culture Medium 22 28 26 39 38 36 25 24 29 31 29 30 2 26 25 27 34 33 35

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