Question

482: Information generated in a designed experiment:

A. Always results in an analysis of variance table

B. Is based on the fact that the variance of the sum is the sum of the variances

C. Must always be quantitative

D. May be based on values which are not necessarily numerical

Answer #1

information generated in a designed experiment

a. Always results in an analysis of variance table.

There are a few steps that needs to be done while designing an experiment

a. Defining the problem and the quesries that needs to be sorted out

b. Defining the audience on which the research needs to be done

c. Need for conducting research on the assigned sample

d. Decide on the eperiment design that needs to be followed.

In this process, although most of the experimentation part depends on numbers but there are few factors that cant be controllable and varies from time to time.

Therefore all the above factors are taken into considerqation and are analysed based on the data collected

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E419: In performing an analysis of variance in a single factor
experiment, a fundamental assumption which is made is that the:
A. Factor (column) means are equal
B. Factor (column) means are unequal
C. Column variances are equal
D. Column variances are significantly different

The following output summarizes the results for a one-way
analysis of variance experiment in which the treatments were three
different hybrid cars and the variable measured was the miles per
gallon (mpg) obtained while driving the same route. (You
may find it useful to reference the q
table.)
Hybrid 1: x⎯⎯1x¯1 = 30, n1 = 20
Hybrid 2: x⎯⎯2x¯2 = 43, n2 = 15
Hybrid 3: x⎯⎯3x¯3 = 30, n3 = 18
Source of Variation
SS
df
MS
F
p-value...

The following output summarizes a portion of the results for a
two-way analysis of variance experiment with no interaction. Factor
A consists of four different kinds of organic fertilizers,
factor B consists of three different kinds of soil acidity
levels, and the variable measured is the height (in inches) of a
plant at the end of four weeks.
a.
Find the missing values in the ANOVA table. (Carry at
least four decimal places in all intermediate calculations. Do NOT
use...

A one-way analysis of variance experiment produced the following
ANOVA table. (You may find it useful to reference
the q table).
SUMMARY
Groups
Count
Average
Column 1
3
0.66
Column 2
3
1.24
Column 3
3
2.85
Source of Variation
SS
df
MS
F
p-value
Between Groups
8.02
2
4.01
4.09
0.0758
Within Groups
5.86
6
0.98
Total
13.88
8
a. Conduct an ANOVA test at the 5% significance
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Do not reject...

A two-way analysis of variance experiment with no interaction is
conducted. Factor A has three levels (columns) and Factor
B has six levels (rows). The results include the following
sum of squares terms:
SST = 390.8 SSA = 238.5 SSE =
69.9
a. Construct an ANOVA table. (Round
intermediate calculations to at least 4 decimal places. Round
"SS" to 2 decimal places, "MS" to 4 decimal
places, "F" to 3 decimal places.)
b. At the 10% significance level, can you...

At the Company”Z” the cost of the library and information center
has always been charged to the various departments based upon
number of employees. Recently, opinions gathered from the
department managers indicate that the number of engineers within a
department might be a better predictor of library and information
center costs.
Total
library and information center costs are $200,000
Department 1 2 3
Number
of
employees 25 50 12
The
number of
engineers 0 17 2
Which cost estimation method is being used by Company Z?
Account analysis method...

Two Way Analysis of Variance results:
Responses: Recall
Row factor: Vivid
Column factor: Length
ANOVA table
Source
DF
SS
MS
F-Stat
P-value
Vivid
1
0
0
0
1
Length
1
32
32
10.666667
0.0309
Interaction
1
8
8
2.6666667
0.1778
Error
4
12
3
Total
7
52
Means table
1
2
1
5
3
4
2
7
1
4
6
2
4
Is there a significant main effect? If yes, is it a main effect
of vividness, length, or both?...

An analysis of variance experiment produced a portion of the
accompanying ANOVA table. (You may find it useful to
reference the F table.)
a. Specify the competing hypotheses in order to
determine whether some differences exist between the population
means.
H0: μA =
μB = μC =
μD; HA: Not all population
means are equal.
H0: μA ≥
μB ≥ μC ≥
μD; HA: Not all population
means are equal.
H0: μA ≤
μB ≤ μC ≤
μD; HA: Not...

A one-way analysis of variance experiment produced the following
ANOVA table. (You may find it useful to reference
the q table).
SUMMARY
Groups
Count
Average
Column 1
6
0.71
Column 2
6
1.43
Column 3
6
2.15
Source of Variation
SS
df
MS
F
p-value
Between Groups
10.85
2
5.43
20.88
0.0000
Within Groups
3.86
15
0.26
Total
14.71
17
SUMMARY
Groups
Count
Average
Column 1
6
0.71
Column 2
6
1.43
Column 3
6
2.15
ANOVA
Source of Variation...

A two-way analysis of variance experiment with no interaction is
conducted. Factor A has three levels (columns) and Factor
B has seven levels (rows). The results include the
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"SS" to 2 decimal places, "MS" to 4 decimal
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Source
SS
df
MS
F
p-value
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