Lecture 3: Data Visualisation

Comprehensive vocabulary flashcards covering statistical data visualization, distribution evaluation, skewness, kurtosis, and graph interpretation from Lecture 3 of PSYC134.

Stem and leaf plot

A visual data display method where each individual score is divided into a stem (representing the leading digits, such as tens) and a leaf (representing trailing digits, such as units) to reveal the distribution shape while preserving individual raw values.

Boxplot

A standardized visual graph that displays the distribution of continuous data based on a five-number summary: minimum, first quartile ($Q_1$), median, third quartile ($Q_3$), maximum, and any identified outliers.

Interquartile Range (IQR)

A measure of statistical dispersion defined as the range containing the middle $50\%$ of data scores, calculated mathematically as the difference between the upper quartile ($Q_3$) and the lower quartile ($Q_1$).

Normal Distribution

A continuous, symmetrical, bell-shaped probability distribution defined mathematically by its mean ($\mu$) and standard deviation ($\sigma$), where the mean, median, and mode are identical.

Skewness

The measure of asymmetry or deviation from symmetry in a probability distribution, which occurs when extreme scores pull the mean away from the median.

Positively Skewed Distribution

An asymmetrical distribution where extreme positive scores (greater than the mean) create a long right-hand tail, causing the mean to be greater than the median.

Negatively Skewed Distribution

An asymmetrical distribution where extreme negative scores (lower than the mean) create a long left-hand tail, causing the mean to be less than the median.

Skewness Statistic Cut-off

The practical threshold rule where a distribution is classified as skewed if its skewness statistic is less than $-1$ or greater than $1$, and classified as approximately normal when the value falls between $-1$ and $1$.

Kurtosis

A statistical measure of the tailedness of a distribution, quantifying how often and how extremely outliers occur relative to a normal distribution.

Mesokurtic

A distribution possessing a kurtosis value equal to $3$, indicating the baseline tailedness and peak height characteristic of a standard normal distribution.

Leptokurtic

A distribution with positive kurtosis ($\text{Kurtosis} > 3$), characterized by a slender, high central peak and fat tails produced by many or very extreme outliers.

Platykurtic

A distribution with negative kurtosis ($\text{Kurtosis} < 3$), characterized by a broad, flatter central peak and skinny tails resulting from fewer or less extreme outliers.

Density Plot

A variation of a histogram that uses kernel smoothing to visualize the continuous distribution of data over an interval, preventing distortion caused by arbitrary bin counts.

Violin Plot

A data visualization combining a box plot with a rotated kernel density plot on both sides, displaying probability density, median, and interquartile range while revealing multimodal distributions.

Choropleth Map

A geographical data visualization where divided territorial regions are colored, shaded, or patterned using a color progression to represent a statistical variable across different areas.

Bubble Map

A geographic visualization that displays circles over specific regions, where the area of each circle is scaled proportionally to its dataset value, mitigating the visual bias of region size seen on choropleth maps.

Truncated Graph

A misleading graph where the vertical axis baseline does not begin at zero, causing small, non-meaningful differences between groups to appear massive.

Error Bars (95% CI)

Graphical indicators depicting data variability by indicating the range in which an estimated parameter (such as a mean) is expected to fall $95$ times out of $100$; non-overlapping error bars between conditions indicate a statistically significant difference.

Scatterplot

A graph plotting individual bivariate observations on Cartesian axes to visually depict the correlation, direction, and strength of a relationship between two continuous variables.

Coulrophobia

The psychological fear of clowns, examined via heart rate metrics to illustrate exploratory and comparative data visualization techniques.

Visual Placement Rules (Appendix vs. Results)

The academic convention dictating that exploratory visuals used to assess data distributions (such as stem-and-leaf plots, boxplots, and normality histograms) belong in the Appendix, whereas explanatory figures communicating analytical findings (such as bar charts and scatterplots) belong in the Results section.