Making Sense of Statistical Significance: Effect Size & Power

These flashcards cover critical concepts related to effect size, statistical significance, power, and related errors in statistics.

Effect Size

A metric to indicate the magnitude of difference or the size of a result, allowing comparison across studies.

Statistical Significance

A determination that a result is not likely to occur randomly or by chance.

Practical Significance

The importance or relevance of a statistically significant result in a real-world context.

Cohen's d

A measure of effect size that expresses the difference between two group means in terms of standard deviation.

Type I Error (α)

The probability of rejecting the null hypothesis when it is actually true, also known as a 'False Positive'.

Type II Error (β)

The probability of failing to reject the null hypothesis when the research hypothesis is true, also referred to as a 'Miss'.

Statistical Power

The probability that a study will correctly reject the null hypothesis when it is false.

Standard Error of the Mean (SEM)

An estimate of the variability of a sample mean compared to the population mean.

Numerator (Effect Size Calculation)

The size of the raw score difference between groups, where a bigger difference results in a larger effect size.

Denominator (Effect Size Calculation)

The variability in the data, where less variability leads to a larger effect size.