Hypothesis Testing and Population Proportions

These flashcards cover key vocabulary and concepts related to hypothesis testing, including types of hypotheses, test statistics, error probabilities, and population proportions.

Null Hypothesis (H0)

The hypothesis that there is no effect or no difference; it is what we seek to test against.

Alternative Hypothesis (H1)

The hypothesis that proposes an effect or a difference; it represents a change from the null.

Test Statistic

A standardized value that is calculated from sample data during a hypothesis test.

Rejection Region

The range of values for the test statistic that will lead to rejecting the null hypothesis.

Alpha (α)

The probability of making a Type I error, or rejecting the null hypothesis when it is true.

Z-score

A statistical measurement that describes a value's relation to the mean of a group of values, expressed in standard deviations.

Power of a Test

The probability that the test correctly rejects the null hypothesis when the alternative hypothesis is true.

Standard Error (SE)

An estimate of the standard deviation of the sampling distribution of a statistic, commonly used to measure the accuracy of a sample.

Two-Tailed Test

A hypothesis test that determines if a sample is greater than or less than a certain value.

One-Tailed Test

A hypothesis test that determines if a sample is either greater than or less than a certain value, but not both.

Population Proportion (p)

The true proportion of a specific outcome in a population, such as the proportion of pulsars among celestial objects.

Sample Proportion (̂p)

The proportion of a specific outcome observed in a sample, used to estimate the population proportion.