Univariate and Bivariate Data Analysis

These flashcards cover key concepts from the lecture notes on data analysis, including types of data, variable relationships, correlation characteristics, and linear modeling techniques.

Univariate Data

Data that contains only one variable, for example, the height of students.

Bivariate Data

Data that contains 2 variables, for example, the hours that students studied and their average test scores.

Causal Relationship

A relationship where one variable directly affects the other, such as the amount of fertiliser and plant growth.

Associative Relationship

A relationship where variables are linked or occur together but do not cause one another, such as coffee consumption and hours of sleep.

Correlation vs. Causation

The principle that correlation does not always mean causation because another factor may affect both variables, such as hot weather increasing both ice cream sales and drowning rates.

Independent Variable

The variable that is manipulated or categorized, often represented on the $x$-axis (e.g., hours worked or time spent on social media).

Dependent Variable

The variable being tested and measured, often represented on the $y$-axis (e.g., Mary's wage or reported stress levels).

Negative Correlation

A relationship where one variable increases as the other expectedly decreases, such as hours spent training versus the time taken to complete a race.

Line of Best Fit

A single line drawn by eye that runs roughly straight through data plots, balancing half of the points above and below the line.

Extrapolation

The act of using a line of best fit to estimate a value for a variable that is far outside the range of the original data, which is considered inaccurate and unreliable.

Interpolation

The act of using the equation of a line of best fit to determine missing measurements within the range of the existing data points.

Gradient

In a linear relationship represented by $y = mx + b$, it identifies the rate of change, such as a crystal's mass growing by $0.975$ grams daily.

Positive Correlation

A relationship where both variables increase together, such as the number of bedrooms in a house and the house price.