Consider the following 2way ANOVA table. Factor A has 5 levels and factor B has 2 levels.
ANOVA 

Source of Variation 
SS 
df 
MS 
F 
Pvalue 

Factor A (Row factor) 
72207.55 
4 
18051.89 
7.770119 
0.00003 

Factor B (Column factor) 
340.3125 
1 
340.3125 
0.146482 
0.70308 

Interaction (A X B) 
1415 
4 
353.75 
0.152265 
0.96138 

Within 
162627.1 
70 
2323.245 

Total 
236590 
79 
Assuming that all the treatment combinations of factors A and B have an equal number of observations, how many observations(replicates) were made for each of the treatment combinations?
Select one:
a. 6
b. 9
c. 7
d. 8
Consider the following 2way ANOVA table. Factor A has 5 levels and factor B has 2 levels.
ANOVA 

Source of Variation 
SS 
df 
MS 
F 
Pvalue 

Factor A (Row factor) 
72207.55 
4 
18051.89 
7.770119 
0.00003 

Factor B (Column factor) 
340.3125 
1 
340.3125 
0.146482 
0.70308 

Interaction (A X B) 
1415 
4 
353.75 
0.152265 
0.96138 

Within 
162627.1 
70 
2323.245 

Total 
236590 
79 
Based on the above ANOVA table, which factor(s) are significant at α = 0.05 ?
Select one:
a. only factor B
b. Factor B and Iinteraction A X B
c. only factor A
d. factors A and B
A large national bank charges local companies for using their services. A bank official reported the results of a regression analysis designed to predict the bank's charges (Y) measured in dollars per month for services rendered to local companies. One independent variable used to predict service charges to a company is the company's sales revenue (X) measured in millions of dollars. Data for 21 companies was used and the following results are obtained.
Predicted value of Y (Y_{i} hat)= 2,700 + 20X_{i}, Twotail test pvalue = 0.034 (for testing β_{1}) 
Interpret the pvalue for testing whether β_{1} is different from 0, that is regression is significant.
Select one:
a. For every $1 million increase in sales revenue, you expect a service charge to increase $0.034.
b. There is insufficient evidence (at the α = 0.10) to conclude that sales revenue (X) is a useful linear predictor of service charge (Y).
c. There is sufficient evidence (at α = 0.05) to conclude that sales revenue (X) is a useful linear predictor of service charge (Y).
d. Sales revenue (X) is a poor predictor of service charge
Solution1:
n=80
=5*2*8
8 observations per each
d. 8
8
Solution2:
For only factor A.,p<0.05
Meaning Factor A is significant
There is no Factor B and interaction effect as
p>0.05
c. only factor A
c. only factor A
Solution3:
H0:slope=0
Ha:slope not = 0
p=0.034
p<0.05
Reject Ho
Accept Ha
There is a ;linear relationship between bank's charges and sales revenue
c. There is sufficient evidence (at α = 0.05) to conclude that sales revenue (X) is a useful linear predictor of service charge (Y).
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