This vides briefed the meaning, Introduction, Definition, Application, Classification and Types of ANOVA. Video link https://youtu.be/YLHGYVMH2T4 Subscribe to Vision Academy https://www.youtube.com/channel/UCjzpit_cXjdnzER_165mIiw

1. Sundar B. N.
Assistant Professor
Analysis of Variance –
Meaning and Types
ANOVA

2. Introduction to ANOVA
The statistical technique known as “Analysis of Variance”,
commonly referred to by the acronym ANOVA was developed by
Professor R. A. Fisher in 1920’s.
The analysis of variance focuses on variability. Variation is
inherent in nature, so analysis of variance means examining the
variation present in data or parts of data. In other words, analysis of
variance means to find out the cause of variation in the data.
The reason, this analysis is called analysis of variance rather
than multi-group mean analysis (or something like that), is because it
compares group means by analysing comparisons of variance
estimates.

3. Meaning to ANOVA
According to Professor R. A. Fisher, Analysis
of Variance (ANOVA) is "Separation of
variance ascribable to one group of causes
from the variance ascribable to other group".
So, by this technique, the total variation
present in the data are divided into two
components of variation one is due to
assignable causes (between the groups
variability) or other is variation due to chance
causes (within group variability).

4. Application of ANOVA
Analysis of variance facilitates the analysis and interpretation of
data from field trials and laboratory experiments in agriculture and
biological research.
Today, it constitutes one of the principal research tools of the
biological scientists, and its use is spreading rapidly in the social
sciences, the physical sciences, in the engineering, in
management, etc.

5. Why should we use ANOVA
 t-test – compared means from two independent groups
ANOVA is helpful because it possesses an advantage over a two
sample t-test. The multiple two sample t-test would result in an
increase of chance of committing a type I error
The analysis of variance technique solves the problems of
estimating and testing to determine, whether to infer the existence
of true difference among "treatment" means, among variety means
and under certain conditions among other means with respect to
the problem of estimation.

6. Classification of ANOVA
Assumption of Additivity
Add Contents Title
Parametric ANOVA
Non Parametric ANOVA
Assumption of Randomness
Assumption of Normality

7. Types of ANOVA
If we consider, only
one independent
variable which affects
the response /
dependent variable.
One-way ANOVA
If the independent
variables/explanatory
variables are more than one
i.e. n (say) then it is called
n-way ANOVA. If n is equal
to two than the ANOVA is
called Two-way classified
ANOVA
Two-way classified
ANOVA
is used when the
experimenter wants
to study the
interaction effects
among the
explanatory
variables
Factorial ANOVA
is used when the
same subjects
(experimental units)
are used for each
treatment (levels of
explanatory
variable).
Repeated measure
ANOVA
Multivariate analysis
of variance (MANOVA)
is used when there
is more than one
response variable.

8. Reference
Prasad, J. (2017). “Unit-5 Introduction to Analysis of Variance.
IGNOU

9. Thank You