# Types of Experimental Designs in Statistics Completely Randomized Design (CRD), Randomized Block Design (RBD), Latin Square Design (LSD) – Advantages and Disadvantages

In the previous post, we have discussed the Principles of Experimental Designs. There we discussed the concept of Experimental design in statistics and their applications. In the present post, we will discuss different types of statistical experimental designs, its applications, advantages and limitations.

## Different types of Experimental Designs

Ø  Experimental designs are broadly classified into TWO categories:

(A).   Single-Factor Experiments

(B).  Multi-factor Experiments

(A). Single-Factor Experiments:

Ø  Single factor experiments are those experiments in which only a single factor varies while all others are kept constant.

Ø  Here the treatments consist exclusively of the different levels of the single variable factor.

Ø  All other factors are applied uniformly to all plots.

Ø  Examples of Single-Factor Experimental Designs:

(1). Completely Randomized Design (CRD)

(2). Randomized Block Design (RBD)

(3). Latin-Square Design (LSD)

# Experimental Designs in Statistics (The Principles of Experimental Designs in Research Methodology)

What is a statistical experiment?

Ø  An experiment is a plan for the collection and analysis of data.

Ø  “It is a controlled act through which data are collected according to some pre-determined objective”.

Ø The observations obtained from a carefully planned and well-designed experiment in advance only gives valid inferences.

Ø An experimental design which gives the smallest error is supposed to be the best design for a particular type of investigation.

Experimental unit (Experimental Plot):

Ø  The smallest division of the experimental material to which we apply the treatment and can make the observation on it is called experimental unit or experimental plot

Treatments:

Ø  Treatments are the characteristics which are to be investigated through an experiment.

Ø  The treatments are the objects of comparisons in an experiment.

Ø  Example: effects of different fertilizers, the yield of different varieties of a crop, disease resistance of different cultivars etc.