ANOVA (analysis of variance) is a statistical method used to compare the means of two or more groups. It divides the variation in a data set into distinct components. The two main types of ANOVA are one-way and repeated measures. One-way ANOVA has one independent factor with at least two levels, while repeated measures has one dependent factor with at least two levels. To perform ANOVA, null and alternative hypotheses are defined along with the significance level. Degrees of freedom, sum of squares, mean squares, and the F-statistic are calculated to determine whether to reject or fail to reject the null hypothesis.

1. ANOVA
It is analysis of variance, a statistical method in which
the variation in a set of observations is divided into
distinct components.
It is a statically model to compare the mean of two and
more than two groups.

2. There are two terms here we are using in ANOVA
1.Factor ( Variable )
2.Levels ( number of groups)

3. Types of ANOVA:
Manly there are two types of ANOVA
1.One way ANOVA : Having one factor with at least
two levels and levels are independent
Eg. There are three sample
0mg, 50mg and 100mg. These three samples are
independent from each other
2. Repeated-Measured : Having one factor with at
least two levels and levels are dependent
Eg. Doing experiment on same data at different
time like day 1 , day 2, and day 3…

5. For doing any testing operation we
need to defined the hypothesis

6. Effect in ANOVA

8. There are seven terms use to test the
ANOVA

9. 1. Define Null and Alternate Hypothesis:
Ho = µ0 mg = µ50 mg. = µ100 mg.
H1 = Not all average are equal.
2. Define alpha
α = 0.05

10. 3.Degree of freedom:
here there are three degree of freedom

11. 4. Decision rule
• Here we can find the value of F from the F table
We make pair of (df of between , df of within)and
then match these value from table, in table
The df of between value will take from vertically
and df of within will take from horizontally. here df of
between is 2 and df of within is 18, so my pair is (2,18)
and we will see in table in second column and 18th
rows. And that value is 3.5546.
If F(calculated ) is greater than the F(tabulated) value then
Null Hypothesis will rejected otherwise accepted.

14. Here there are four terms we have to find ss(sum of
square),df( degree of freedom) ,MS(mean
square),and F

20. Here given alpha is = 0.05