Unit 2 Flashcard #1: Pesky Statistics Terminology

Front

What does an alpha level of 0.05 signify in hypothesis testing?

Back

An alpha level of 0.05 indicates a 5% risk of concluding that a difference exists when there is no actual difference (Type I error).

Front

What is the null hypothesis?

Back

The null hypothesis is a statement that there is no effect or no difference, and it serves as the default assumption in hypothesis testing.

Front

What is a dependent t-test used for?

Back

A dependent t-test is used to compare the means of two related groups to determine if there is a statistically significant difference between them.

Front

What is an independent variable?

Back

An independent variable is the variable that is manipulated or controlled in an experiment to test its effects on the dependent variable.

Front

What is a directional alternative hypothesis?

Back

A directional alternative hypothesis specifies the direction of the expected difference between groups, indicating that one group will have a greater or lesser mean than the other.

Front

What does it mean to fail to reject the null hypothesis?

Back

Failing to reject the null hypothesis means that there is not enough evidence to support the alternative hypothesis, suggesting that any observed differences may be due to chance.

Front

What is a p-value?

Back

A p-value is the probability of obtaining test results at least as extreme as the observed results, assuming that the null hypothesis is true.

Front

What is the significance of a p-value less than 0.05?

Back

A p-value less than 0.05 typically indicates strong evidence against the null hypothesis, leading to its rejection.

Front

What is the difference between a one-tailed and a two-tailed test?

Back

A one-tailed test assesses the direction of the effect (greater or lesser), while a two-tailed test assesses whether there is any difference, regardless of direction.

Front

What is the purpose of a control group in an experiment?

Back

A control group serves as a baseline to compare against the experimental group, helping to isolate the effect of the independent variable.