Basic Statistics - Z-Scores and the Normal Curve Model

This set of flashcards covers key vocabulary and concepts related to Z-Scores and Normal Distribution as presented in Basic Statistics for the behavioral sciences.

Absolute Value

The size of a number regardless of its sign; e.g., the absolute value of +2 is 2 and -2 is 2.

Z-Score

A statistic that measures the deviation of a score from the mean, expressed in standard deviations.

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.

Standard Deviation

A measure of the amount of variation or dispersion of a set of values.

Measures of Central Tendency

Statistics that describe the center of a data set, commonly including mean, median, and mode.

Measures of Variability

Statistics that describe the spread of a data set, including range, variance, and standard deviation.

Relative Standing

A position of a score in relation to the rest of the data in a sample.

Percentile

A measure indicating the value below which a given percentage of observations in a group fall.

Central Limit Theorem

A statistical theory that states that the sampling distribution of the sample means approaches a normal distribution as the sample size increases.

Standard Error of the Mean

A measure of how much the sample mean would vary from the population mean if multiple samples were taken.

Z-Distribution

The distribution resulting from transforming all raw scores into z-scores, allowing for comparison of scores across different distributions.

Transforming Raw Scores to Z-Scores

A process that combines the concepts of central tendency and variability to locate a particular score in comparison to the overall distribution.

Frequency Distribution

A summary of how often each different value occurs in a dataset.

Negative Skew

A distribution in which most values are concentrated on the right, with a tail extending to the left.

Transforming Scores into Z-Distributions

Standardizing raw scores to a single scale to compare different metrics.

Raw Score

The original untransformed score obtained from a measurement.

Comparing Apples to Oranges

Evaluating scores from different distributions by transforming them into a common metric (z-scores).