Sampling Distribution and Hypothesis Testing

These flashcards cover key concepts related to sampling distributions, hypothesis testing, and statistical errors.

Sampling Error

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

Central Limit Theorem

The distribution of sample means will approach a normal distribution as the sample size increases, typically around n = 30.

Standard Error of the Mean (SEM)

The standard deviation of the sampling distribution of the mean, providing a measure of how much a sample mean is expected to vary from the population mean.

Hypothesis Testing

A statistical method that uses sample data to evaluate a hypothesis about a population, aiming to rule out chance as an explanation for research results.

Null Hypothesis (Ho)

The hypothesis that there is no effect or no difference and serves as a basis for statistical testing.

Alpha Level (α)

The criterion established for making a decision about the null hypothesis, determining the risk of committing a Type I error.

Type I Error

Occurs when a researcher rejects a true null hypothesis, concluding that a treatment has an effect when it does not.

Type II Error

Occurs when a researcher fails to reject a false null hypothesis, missing a real treatment effect.

Effect Size (Cohen's d)

A measure used to evaluate the size of the difference between means, indicating the practical significance of a result.

Z-score

A statistic that indicates how many standard deviations an element is from the mean, used in hypothesis testing.

Distribution of Sample means

collection of sample means for all the possible random samples of a particular size (n) that can be obtain and from a population.

What happens when n > 30?

Distribution is approximately normal.

Law of large numbers

The larger the sample size (n), the more probable is that the sample means will be close to the population mean.

What affects the shape of the sampling distribution?

Sample size and population distribution.