**Randomized block design**

A
randomized block design (RBD) is a design in which the whole set of
experimental units arranged in several blocks which are internally homogeneous
and extremely heterogeneous and then the selected treatments are randomly
allocated to the experimental units within each block such that each treatment
occurs one or same number of times in each block.

**Advantages of RBD**

i) RBD
is more efficient than CRD and thus provides more accurate and precise results
than CRD.

ii) Any
number of blocks and any number of treatments can be used in RBD except the
restriction that at least two replicates are needed to a carry out the test of
significance.

iii) Analysis
of data is simple and straight forward in RBD.

iv) RBD
provides a method of eliminating or reducing the effects of trends.

v) It is
flexible readily adoptable and easy to analyze.

**Disadvantage of RBD**

i) RBD
is not suitable for large number of treatments as large error variation may
arise in such case and when the blocks are within heterogeneous.

ii) Property
of orthogonality is lost by missing values in a RBD leading to complicated
analysis of data.

iii) RBD
has less error than comparable to
CRD.

iv) Since
RBD controls variability due to one extraneous factor it is unsatisfactory when
several extraneous factor exists among the experimental unit.

v) The
efficiency of RBD decreases as the block size increases.

**Reasons of blocking**

i) One
major reason for use of blocks is to make inferences over a large number of
environmental conditions.

ii) Another
major reason is to reduce error variation by removing an unwanted source of
variation from error variation.

**Uses of RBD**

i) RBD
removes one extraneous source of variation from experimental error and so
increases precision. Thus RBD is used to increase precision.

ii) Its
use is found to be satisfactory in many experimental situations and thus it
avoids the necessity of using more complex designs.

iii) RBD
provides unbiased estimates of block means in addition to that of treatment
means and thus furnishes additional information from the experiment. It is not
necessary that all blocks be conducted at the same location or at same time.

**In what situation we have to apply RBD?**

CRD
is appropriate only for experiments having homogeneous experimental units and a
small number of treatments. In experiments having heterogeneous experimental
units and large number of treatments randomized block design is appropriate. It
specially is used to control the heterogeneity and variability among the
experimental units involving blocks as local control measure. If CRD is used in
situations having heterogeneous experimental units, then the variation in
yields form different experimental units can no longer be appropriate.

**Why we use one tail test in analysis of variance.**

Suppose
we want to test the following hypothesis

To
test the hypothesis we use the following statistic

which
follows distribution under with and

Relatively
large values of Treatment reflecting real
differences among the treatments produce large values of statistic and so lead
to the rejection of null hypothesis. Thus upper tail of distribution serves as
critical region for the null hypothesis of no differences among the treatments
and hence one tail test is used in
analysis of variance. In fact, the greater the differences between the and , the greater is the evidence that corresponding treatment
means are different. So relatively large values of provides greater
evidence favoring rejection of the hypothesis of no treatment differences.