One-Way ANOVA

One-Way ANOVA

One-Way ANOVA

Description

It compares the mean values of three or more independent groups in order to determine the statistical evidence that the associated population means are significantly different.

Why to use

To perform analysis of variance.

When to use

Equality testing between three or more population means.

When not to use

Equality testing between only two population means.

Prerequisites

Independent variables should be numerical.

Input

Any dataset that contains numerical data.

Output

  • Degrees of Freedom
  • Sum of Squares
  • Mean Sum of Squares
  • F-Ratio

Statistical Methods used

  • Sum of Squares
  • Mean Sum of Squares
  • Shapiro Wilk Test
  • Bartlett Test of homogeneity

Limitations

  • It cannot be used on any data other than numerical.
  • It cannot be used for more than one dependent variable.

One Way ANOVA is a statistical analysis method. It is used to determine if there are any statistical differences in three or more samples' mean values.

In One-Way ANOVA,

Null Hypothesis – All the samples have an equal mean.

Alternative Hypothesis – All the samples do not have equal means.

One-Way ANOVA tests the Null Hypothesis(H0),

H0: µ0 = µ1 = µ2 = µ3 = … = µk

Where,

µ = the group mean

k = number of samples

Suppose One-Way ANOVA returns a significant result. In that case, we accept the alternative hypothesis: at least two groups have mean values that are significantly different from each other.

However, it cannot tell which groups have significantly different means.

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