wk 4: Normal Distribution and Z-Scores

These flashcards cover key vocabulary terms related to normal distribution, Z-scores, sampling, and confidence intervals, essential for understanding statistics.

Normal Distribution

A probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean.

Z-Score

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

Empirical Rule

A statistical rule stating that for a normal distribution, nearly all data will fall within three standard deviations of the mean.

Confidence Interval

A range of values so defined that there is a specified probability that the value of a parameter lies within it.

Standard Error of the Mean (SEM)

An estimate of how far the sample mean is likely to be from the population mean, calculated as the standard deviation divided by the square root of the sample size.

Sampling Error

The difference between the sample statistic and the population parameter that arises due to the randomness of sampling.

Central Limit Theorem (CLT)

A theorem stating that the distribution of sample means approaches a normal distribution as the sample size becomes larger, typically n=30 or more.

Standard Normal Distribution

A normal distribution with a mean of 0 and a standard deviation of 1, often used to compare different data points.

Sampling Distribution

A probability distribution of all possible sample means from a population.

Symmetric Distribution

A distribution in which the left side mirrors the right side equally around the center.