Study Guide: Correlation, t-Tests, and ANOVA

Flashcards covering key concepts related to correlation, t-tests, and ANOVA for exam preparation.

What is the purpose of correlation in statistics?

Measures how two or more variables change together and helps predict one variable based on another.

What indicates a positive correlation?

Both variables increase together.

What does a correlation coefficient (r) range from?

It ranges from -1.0 to +1.0, where values closer to ±1 indicate a strong relationship and values closer to 0 indicate a weak relationship.

When is a correlation considered significant?

If p < 0.05, it indicates a significant relationship.

What does the coefficient of determination (r²) represent?

It shows the shared variance or percentage of overlap between variables.

What is the formula for linear regression?

Y = a + bX.

What is the purpose of a t-test?

To test if the means of two groups differ significantly.

What is an independent t-test?

It compares two unrelated groups.

What is a Type I error in hypothesis testing?

A false positive - rejecting a true null hypothesis.

What does ANOVA compare?

It compares the means of 3 or more groups.

What is the decision rule for ANOVA when the calculated F is greater than the critical F?

Reject the null hypothesis.

What are post-hoc tests used for in ANOVA?

To identify which specific groups differ from each other.

What is ANCOVA?

ANOVA that controls for covariates to account for pre-existing differences.

What is the main decision rule for determining significance across correlation, t-tests, and ANOVA?

Compare the p-value to α (0.05) to determine significance.