The Difference Between t-tests and ANOVAs

The Difference Between t-tests and ANOVAs

1. The difference between t-tests and ANOVAs is that t-tests are used to analyze data from independent variables with just two levels Whereas ANOVAs are used to analyze data from independent variables with three or more levels For example – studying driving speed across two levels of athlete (football and basketball players). For example – studying driving speed across three levels of athlete (football, basketball, soccer players). NEXT Differentiating Parametric Tests that Capture Differences Between Groups

2. T-test Family Single sample t-test – compares a single sample with its supposed population Independent samples t-test – compares one sample with another sample Paired-samples t-test – compares one sample on “time one” with itself on “time two” Differentiating Parametric Tests that Capture Differences Between Groups Sample Population generalize Sample 1 Sample 2 c ompared with Sample 1 Sample 1 c ompared with Time 1 Time 2 NEXT

3. ANOVA Family One-way ANOVA – compares at least three samples with one another ANCOVA – compares at least two samples with one another controlling for a covariate One-way Repeated Measures ANOVA – compares one sample on “time one”, “time two” and “time three” with itself . Factorial ANOVA – compares at least two samples on one independent variable and those same samples on another independent variable . Split-Plot ANOVA - compares at least two samples with one another on one independent variable and compares them as well across time . Differentiating Parametric Tests that Capture Differences Between Groups Child Teen Adult Child Teen c ontrolling for Sample 1 Time 1 Sample 1 Time 2 Sample 1 Time 3 Age Ice cream preference across both Gender Age b roken into three levels Age Gender Age Ice cream preference across both Time