What are the differences between T-test and ANOVA?

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Basic of Differentiation
T-test
ANOVA (analysis of variance)

Definition
T test is a statistical hypothesis test used to determine whether or not there is a statistically significant difference between the means of two populations 
ANOVA is a statistical technique used to determine whether or not there is a statistically significant difference between the means of three or more populations

When the test is used
Is used to compare the means of two groups
Is used to compare the means of three or more groups

Types of tests
Two types of t-tests:  Independent samples t-test and Paired samples t-test
Two types of ANOVA tests: One-way ANOVA and two-way ANOVA

Purpose
Used for pure hypothesis testing purposes
Used to examine standard deviations

Population size
Used when population is less than 30
Used for larger populations

Potential for error
Less likely to have errors
Higher risk of errors

Use of single-sided or double sided test
Can be performed in a single-sided or double-sided test
Can be performed only as a one-sided test because of no negative variance

Basic of Differentiation	T-test	ANOVA (analysis of variance)
Definition	T test is a statistical hypothesis test used to determine whether or not there is a statistically significant difference between the means of two populations	ANOVA is a statistical technique used to determine whether or not there is a statistically significant difference between the means of three or more populations
When the test is used	Is used to compare the means of two groups	Is used to compare the means of three or more groups
Types of tests	Two types of t-tests: Independent samples t-test and Paired samples t-test	Two types of ANOVA tests: One-way ANOVA and two-way ANOVA
Purpose	Used for pure hypothesis testing purposes	Used to examine standard deviations
Population size	Used when population is less than 30	Used for larger populations
Potential for error	Less likely to have errors	Higher risk of errors
Use of single-sided or double sided test	Can be performed in a single-sided or double-sided test	Can be performed only as a one-sided test because of no negative variance

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