Statistics and probability


Data are characteristics or information, usually numerical, that are collected through observation. In a more technical sense, data are a set of qualitative or quantitative variables about one or more persons or objects, while a datum (singular of data) is a single value of a single variable.


Types of Data

Qualitative data: is non-numerical, eg “it was fun", "blue".

Quantitative data: is numerical. Quantitative data can be discrete or continuous.

Discrete data: is data which takes specific (discrete) values, eg “number of accidents”, "points in the IB diploma".

Continuous data: is data which can take a full range of values, eg "height", “speed".


Data Samples and error visualization techniques | by Anthony Figueroa |  Towards Data Science

Population: all members of a defined group.
Sample: a subset of the population, a selection of individuals from the population.

Biased sampling is where the method may cause you to draw misleading conclusions about the population.


Survivorship Bias - an example of biased sampling.


Types of sampling

Simple random sampling: every member of the population is equally likely to be chosen. For example, allocate each member of the population a number. Then use random numbers to choose a sample.

Systematic sampling: find a sample of size \(n\) from a population of size \(N\) by selecting every \(k\)th member where \(k = \frac{N}{n}\) to the nearest whole number.

Stratified sampling: is selecting a random sample where numbers in certain categories proportional to the numbers in the population. (E.G. in polls)


Stratified Polling in New Zealand


Mean, Median, Mode


Standard Deviation (TBC)



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