Normal Distribution and Z-Scores

These flashcards cover key vocabulary and concepts related to normal distribution, z-scores, and statistical analysis methods.

Normal Distribution

A symmetrical distribution of scores around the mean with a small number of outliers.

Standardized Normal Distribution (Z-distribution)

A normal distribution with a mean of 0 and standard deviation of 1.

Z-score

A statistical measurement indicating how many standard deviations a data point is from the mean.

Skewness

A measure of the asymmetry of a distribution; can be positively or negatively skewed.

Kurtosis

The degree of peakedness of a frequency distribution, related to the spread of scores.

Empirical Rule

States that for a normal distribution, about 68% of values lie within 1 SD, 95% within 2 SDs, and 99.7% within 3 SDs of the mean.

Frequency Distribution

A summary of how often different values occur within a dataset, typically displayed in tables or graphs.

Normal Curve

A theoretical frequency distribution that is symmetrical, unimodal, and has equal mean, median, and mode.

Shapiro-Wilk’s W test

A formal test of normality that assesses whether a variable's distribution is skewed or kurtotic.

Positive Skewness

When the largest portion of data is below the mean, resulting in a longer right tail.

Negative Skewness

When the largest portion of data is above the mean, resulting in a longer left tail.

Outlier

A data point that is significantly different from the other observations in a dataset.

Standard Deviation (SD)

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

Hypothesis Testing

A statistical method for testing a hypothesis about a parameter in a population.

Nonparametric Statistics

Statistical analyses that do not assume a specific distribution for the data.

Histogram

A graphical representation of the distribution of numerical data, showing the number of occurrences for data intervals.