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MODULE - II
LECTURE - 9
BALANCED INCOMPLETE BLOCK 
DESIGN (BIBD)
Dr. Shalabh
Department of Mathematics & Statistics
Indian Institute of Technology Kanpur
Analysis of Variance and 
Design of Experiments-II
Page 2


MODULE - II
LECTURE - 9
BALANCED INCOMPLETE BLOCK 
DESIGN (BIBD)
Dr. Shalabh
Department of Mathematics & Statistics
Indian Institute of Technology Kanpur
Analysis of Variance and 
Design of Experiments-II
The designs like CRD and RBD are the complete block designs. We now discuss the balanced incomplete block design
(BIBD) and the partially balanced incomplete block design (PBIBD) which are the incomplete block designs.
2
A balanced incomplete block design (BIBD) is an incomplete block design in which
? b blocks have the same number k of plots each and
? every treatment is replicated r times in the design.
? Each treatment occurs at most once in a block, i.e., or 1  where is the number of times the j
th
treatment 
occurs in i
th
block,  i = 1, 2,…, b;  j = 1, 2,…, v.
? Every pair of treatments occurs together is of the b blocks . 
0
ij
n =
ij
n
?
Such design is denoted by 5 parameters                      .
The parameters                         are not chosen arbitrarily.
They satisfy the following relations:
(, , , ; ) Db k v r ?
, , , and bk v r ?
()
( ) ( 1) ( 1)
( ) ( ).
   
  
 andhence
I bk vr
II v r k
III b v r k
?
=
-= -
= >
,
,
ij
j
ij
j
nk i
nr j
=
=
?
?
Hence for all
for all
     
    
and   for all   Obviously         cannot be a constant for all j.  So the design is not 
orthogonal.
'
1' 2 '
...
jj
j ij j ij b b
nn n n n n ? + ++ =
' 1,2,..., . jj v ?=
ij
n
r
Page 3


MODULE - II
LECTURE - 9
BALANCED INCOMPLETE BLOCK 
DESIGN (BIBD)
Dr. Shalabh
Department of Mathematics & Statistics
Indian Institute of Technology Kanpur
Analysis of Variance and 
Design of Experiments-II
The designs like CRD and RBD are the complete block designs. We now discuss the balanced incomplete block design
(BIBD) and the partially balanced incomplete block design (PBIBD) which are the incomplete block designs.
2
A balanced incomplete block design (BIBD) is an incomplete block design in which
? b blocks have the same number k of plots each and
? every treatment is replicated r times in the design.
? Each treatment occurs at most once in a block, i.e., or 1  where is the number of times the j
th
treatment 
occurs in i
th
block,  i = 1, 2,…, b;  j = 1, 2,…, v.
? Every pair of treatments occurs together is of the b blocks . 
0
ij
n =
ij
n
?
Such design is denoted by 5 parameters                      .
The parameters                         are not chosen arbitrarily.
They satisfy the following relations:
(, , , ; ) Db k v r ?
, , , and bk v r ?
()
( ) ( 1) ( 1)
( ) ( ).
   
  
 andhence
I bk vr
II v r k
III b v r k
?
=
-= -
= >
,
,
ij
j
ij
j
nk i
nr j
=
=
?
?
Hence for all
for all
     
    
and   for all   Obviously         cannot be a constant for all j.  So the design is not 
orthogonal.
'
1' 2 '
...
jj
j ij j ij b b
nn n n n n ? + ++ =
' 1,2,..., . jj v ?=
ij
n
r
Example of BIBD
3
1 10 1 6
( , ; , ; ) : 10 ( , ,..., ), 6 ( , ,..., ), 3, 5, 2 Db k v r b B B v T T k r ? ? = = = = = In the design consider say say       
1 12 3
2 12 4
3 13 5
4 14 6
5 1 56
6 2 36
7 2 45
8 256
9 345
10 3 4 6
Blocks  Treatments
B
B
B
B
B
B
B
B
B
B
Now we see how the conditions of BIBD are satisfied.
( ) 10 3 30 6 5 30
( ) ( 1) 2 5 10 ( 1) 5 2 10
( 1) ( 1)
( ) 10 6
i bk vr
bk vr
ii v r k
v rk
iii b
?
?
= ×= = × =
? =
-= × = -= × =
? -= -
= =
and
and
    
  
   
  
 
Page 4


MODULE - II
LECTURE - 9
BALANCED INCOMPLETE BLOCK 
DESIGN (BIBD)
Dr. Shalabh
Department of Mathematics & Statistics
Indian Institute of Technology Kanpur
Analysis of Variance and 
Design of Experiments-II
The designs like CRD and RBD are the complete block designs. We now discuss the balanced incomplete block design
(BIBD) and the partially balanced incomplete block design (PBIBD) which are the incomplete block designs.
2
A balanced incomplete block design (BIBD) is an incomplete block design in which
? b blocks have the same number k of plots each and
? every treatment is replicated r times in the design.
? Each treatment occurs at most once in a block, i.e., or 1  where is the number of times the j
th
treatment 
occurs in i
th
block,  i = 1, 2,…, b;  j = 1, 2,…, v.
? Every pair of treatments occurs together is of the b blocks . 
0
ij
n =
ij
n
?
Such design is denoted by 5 parameters                      .
The parameters                         are not chosen arbitrarily.
They satisfy the following relations:
(, , , ; ) Db k v r ?
, , , and bk v r ?
()
( ) ( 1) ( 1)
( ) ( ).
   
  
 andhence
I bk vr
II v r k
III b v r k
?
=
-= -
= >
,
,
ij
j
ij
j
nk i
nr j
=
=
?
?
Hence for all
for all
     
    
and   for all   Obviously         cannot be a constant for all j.  So the design is not 
orthogonal.
'
1' 2 '
...
jj
j ij j ij b b
nn n n n n ? + ++ =
' 1,2,..., . jj v ?=
ij
n
r
Example of BIBD
3
1 10 1 6
( , ; , ; ) : 10 ( , ,..., ), 6 ( , ,..., ), 3, 5, 2 Db k v r b B B v T T k r ? ? = = = = = In the design consider say say       
1 12 3
2 12 4
3 13 5
4 14 6
5 1 56
6 2 36
7 2 45
8 256
9 345
10 3 4 6
Blocks  Treatments
B
B
B
B
B
B
B
B
B
B
Now we see how the conditions of BIBD are satisfied.
( ) 10 3 30 6 5 30
( ) ( 1) 2 5 10 ( 1) 5 2 10
( 1) ( 1)
( ) 10 6
i bk vr
bk vr
ii v r k
v rk
iii b
?
?
= ×= = × =
? =
-= × = -= × =
? -= -
= =
and
and
    
  
   
  
 
Even if the parameters satisfy the relations, it is not always possible to arrange the treatments in blocks to get the
corresponding design.
The necessary and sufficient conditions to be satisfied by the parameters for the existence of a BIBD are not known.
The conditions (I)-(III) are some necessary condition only. The construction of such design depends on the actual
arrangement of the treatments into blocks and this problem is addressed in combinatorial mathematics. Tables are available
giving all the designs involving at most 20 replications and their methods of construction.
4
Page 5


MODULE - II
LECTURE - 9
BALANCED INCOMPLETE BLOCK 
DESIGN (BIBD)
Dr. Shalabh
Department of Mathematics & Statistics
Indian Institute of Technology Kanpur
Analysis of Variance and 
Design of Experiments-II
The designs like CRD and RBD are the complete block designs. We now discuss the balanced incomplete block design
(BIBD) and the partially balanced incomplete block design (PBIBD) which are the incomplete block designs.
2
A balanced incomplete block design (BIBD) is an incomplete block design in which
? b blocks have the same number k of plots each and
? every treatment is replicated r times in the design.
? Each treatment occurs at most once in a block, i.e., or 1  where is the number of times the j
th
treatment 
occurs in i
th
block,  i = 1, 2,…, b;  j = 1, 2,…, v.
? Every pair of treatments occurs together is of the b blocks . 
0
ij
n =
ij
n
?
Such design is denoted by 5 parameters                      .
The parameters                         are not chosen arbitrarily.
They satisfy the following relations:
(, , , ; ) Db k v r ?
, , , and bk v r ?
()
( ) ( 1) ( 1)
( ) ( ).
   
  
 andhence
I bk vr
II v r k
III b v r k
?
=
-= -
= >
,
,
ij
j
ij
j
nk i
nr j
=
=
?
?
Hence for all
for all
     
    
and   for all   Obviously         cannot be a constant for all j.  So the design is not 
orthogonal.
'
1' 2 '
...
jj
j ij j ij b b
nn n n n n ? + ++ =
' 1,2,..., . jj v ?=
ij
n
r
Example of BIBD
3
1 10 1 6
( , ; , ; ) : 10 ( , ,..., ), 6 ( , ,..., ), 3, 5, 2 Db k v r b B B v T T k r ? ? = = = = = In the design consider say say       
1 12 3
2 12 4
3 13 5
4 14 6
5 1 56
6 2 36
7 2 45
8 256
9 345
10 3 4 6
Blocks  Treatments
B
B
B
B
B
B
B
B
B
B
Now we see how the conditions of BIBD are satisfied.
( ) 10 3 30 6 5 30
( ) ( 1) 2 5 10 ( 1) 5 2 10
( 1) ( 1)
( ) 10 6
i bk vr
bk vr
ii v r k
v rk
iii b
?
?
= ×= = × =
? =
-= × = -= × =
? -= -
= =
and
and
    
  
   
  
 
Even if the parameters satisfy the relations, it is not always possible to arrange the treatments in blocks to get the
corresponding design.
The necessary and sufficient conditions to be satisfied by the parameters for the existence of a BIBD are not known.
The conditions (I)-(III) are some necessary condition only. The construction of such design depends on the actual
arrangement of the treatments into blocks and this problem is addressed in combinatorial mathematics. Tables are available
giving all the designs involving at most 20 replications and their methods of construction.
4 5
()
( ) ( 1) ( 1)
() .
I bk vr
II v r k
III b v
?
=
-= -
=
Proof: (I) 
Let incidence matrix.
Observing that the quantities  are the scalars and the transpose of each other, we find their values. 
Consider
( ):
ij
N n bv = ×
Theorem
11 1 1
'
bv v b
E NE E N E and
11 21 1
12 22 2
11
12
1
2
1
1
1
(1,1,...,1)
  
1
(1,1,...,1)
(1,1,...,1)
 .
b
b
bv
v v bv
j
j
j
j
bj
j
b
nn n
nn n
E NE
nn n
n
n
n
k
k
k
bk
×
? ?? ?
? ?? ?
? ?? ?
=
? ?? ?
? ?? ?
? ? ? ?
? ?
? ?
? ?
? ?
=
? ?
? ?
? ?
? ?
? ?
??
??
??
=
??
??
??
=
?
?
?
?
?
? ? ? ??
?
?
?
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FAQs on Balanced Incomplete Block Design (BIBD), Analysis of Variance and Design of Experiments-II - Computer Science Engineering (CSE)

1. What is a Balanced Incomplete Block Design (BIBD)?
Ans. A Balanced Incomplete Block Design (BIBD) is a statistical design used in experiments to study the effects of multiple factors on a response variable. It is characterized by a set of treatments, blocks, and units, where each treatment appears exactly once in each block and each unit is assigned to only one treatment within a block. The design is balanced because each treatment occurs the same number of times and incomplete because not every pair of treatments is compared in every block.
2. How is Analysis of Variance (ANOVA) used in the context of BIBD?
Ans. Analysis of Variance (ANOVA) is a statistical technique used to determine if there are significant differences among the means of multiple groups. In the context of a Balanced Incomplete Block Design (BIBD), ANOVA can be used to assess the effects of different factors on the response variable. By partitioning the total variation in the data into variations due to the treatments, blocks, and error, ANOVA helps in identifying whether the observed differences in the response variable are statistically significant or merely due to chance.
3. What are the advantages of using BIBD in experimental design?
Ans. Balanced Incomplete Block Designs (BIBDs) offer several advantages in experimental design. Firstly, they allow for efficient utilization of resources by reducing the number of treatments and replicates required compared to a complete design. Secondly, BIBDs enable the study of multiple factors and their interactions within a limited number of experimental units. Additionally, BIBDs can help in controlling for confounding variables and improving the accuracy of estimates by incorporating blocking factors. Overall, BIBDs provide a cost-effective and statistically robust approach to experimental design.
4. How can BIBD be applied in the field of Computer Science Engineering (CSE)?
Ans. In the field of Computer Science Engineering (CSE), Balanced Incomplete Block Designs (BIBDs) can be applied to various research areas. For example, BIBDs can be used to evaluate the performance of different algorithms or software systems by assigning them as treatments and measuring their impact on specific performance metrics. BIBDs can also be used to analyze the effects of different configurations or settings on the efficiency or reliability of computer networks or distributed systems. The flexibility and efficiency of BIBDs make them a valuable tool for experimental design in CSE.
5. What is the relationship between BIBD and Design of Experiments (DOE)?
Ans. Balanced Incomplete Block Designs (BIBDs) are a type of experimental design technique that falls under the broader framework of Design of Experiments (DOE). DOE encompasses various statistical methods and principles used to systematically plan, conduct, analyze, and interpret experiments. BIBDs, along with other designs such as completely randomized designs and factorial designs, are specific strategies within DOE that help researchers make efficient use of resources and obtain reliable results. In summary, BIBDs are a specialized approach within the broader field of Design of Experiments.
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