Chapter 7 | Probability and Samples: The Distribution of Sample Means

These flashcards cover key concepts and terminology from Chapter 7 on the probability and distribution of sample means.

Distribution of Sample Means

The collection of sample means for all possible random samples of a particular size from a population.

Sampling Distribution

A distribution of statistics obtained by selecting all possible samples of a specific size from a population.

Central Limit Theorem

States that the distribution of sample means for a sample size n will have a mean equal to the population mean and will approach a normal distribution as n increases.

Sampling Error

The natural discrepancy, or amount of error, between a sample statistic and its corresponding population parameter.

Law of Large Numbers

States that large samples will be more representative of the population from which they are selected.

Z-Score for Sample Means

Describes how a sample mean relates to the population mean using the formula z = (M - m) / sM.

Standard Error (sM)

The standard deviation of the distribution of sample means, indicating the expected difference between sample mean and population mean.

Cohen’s d

A measure of effect size that indicates the standardized difference between two means.

Power of a Test

The probability that the test will correctly reject the null hypothesis if it is false.

Type I Error

Rejecting a true null hypothesis - concluding a treatment effect when none exists.

Type II Error (β)

Failing to reject a false null hypothesis - not detecting a treatment effect that actually exists.

Sample Size (n)

The number of observations or individuals included in a sample, affecting the reliability of the sample mean.

Null Hypothesis (H0)

A statement predicting no effect or no difference; typically represents the status quo.

Alternative Hypothesis (H1)

A statement predicting an effect or difference; the hypothesis that researchers seek to support.

Critical Region

The area in a statistical distribution where, if a test statistic falls within it, the null hypothesis is rejected.

Confidence Interval

A range of values around a sample estimate that is likely to contain the population parameter.