IB Maths AI 4.1 Definitions

This page contains our IB Maths AI definitions for 4.1. By learning each one of these definitions, you will fully cover the content for IB Maths AI 'Fundamentals of statistics'.

All Topic 4 Sub-topics 4.1: Fundamentals Of Statistics 4.2: Visualising Statistics 4.3: Distribution Properties 4.4: Introduction To Linear Statistics 4.5: Probability 4.6: Probability Distributions 4.7: Hypotheses & Tests (HL)4.8: Data collection & categorisation (HL)4.9: Advanced linear statistics (HL)4.10: Linear transformations & combinations (HL)4.11: Confidence intervals (HL)4.12: Poisson distribution (HL)4.13: Distribution tests (HL)4.14: Transition matrices

bias

A tendency in the sampling or data collection process that favours certain outcomes or groups, so the results are not representative.

continuous

Able to take any value within an interval.

discrete

Taking separate, countable values, usually whole numbers.

frequency

A table that shows how often each value (discrete) or each class interval (continuous) occurs.

modal

The class interval with the highest frequency in grouped data (used when class intervals are equal).

outlier

A value unusually far from the rest of the data; in this course, one that is below

Q_1-1.5\times IQR

or above

Q_3+1.5\times IQR

, where

IQR=Q_3-Q_1

population

The full set of all possible values of interest, described by parameters such as the mean '

\mu

' and variance '

\sigma^2

quartiles

Values that split ordered data into four equal parts; on a cumulative frequency graph with $n$ values, they are estimated at cumulative frequencies $\frac{n}{4}$ and $\frac{3n}{4}$ .

random

Describing an outcome that cannot be predicted with certainty in advance, even though long-run patterns may be modelled using probabilities.

sample

A set of '

n

' observed values taken from a population and used to compute statistics such as '

\bar{x}

' and '

s_{n-1}^2

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