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What are the differences between T-test and ANOVA?
Posted August 17, 2022
Answer
| 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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