## IB Physics Glossary

All categories |

## TOPIC 1: MEASUREMENTS AND UNCERTAINTIES |
---|

## Accuracytells us how close the measured value of a quantity is to its true value. An accurate measurement is "close" to a true value. An inaccurate measurement is "far" from a true value. | |

## Derived units are not fundamental but can be expressed in terms of fundamental units. | |

## Fundamental units are the most basic units which cannot be expressed in terms of other units. The seven fundamental units are 1. meter (m); 2. second (s); 3. kilogram (kg); 4. Kelvin (K); 5. The Ampere (A); 6. mole (mol); 7. candela (cd). | |

## Log-log plots are used to find the value of the exponent $$n$$ and coefficient $$a$$ for the general relationship $$ y= a x^n$$. The value of the gradient for the log-log plot equals $$n$$ and $$a= log^{-1}{(\text{y-intercept})}$$. For example A linear relationship should have $$n \approx 1$$; A square-root relationship should have $$n \approx \frac{1}{2}$$; A quadratic relationship should have value $$n \approx 2$$; An inverse-square relationship should have value $$n \approx -2$$. | |

## Precision tells us how consistent repeated measurements are. A precise set of measurements are relatively closer together. An imprecise set of measurements are spread apart. | |

## Proportional relationship $$y \propto x$$ or $$y = m x$$, occurs when the relationship between $$y$$ and $$x$$ is linear with a zero y-intercept value, that is, a straight line passing through the origin. The x- and y-error bars may allow a range of values for the y-intercept, because the lines of max & min gradients, thus showing a possible proportional relationship for a best-fit straight line even if its y-intercept value is non-zero. Beware, for the IB, a best-fit line can be any curve which fits the data points. It does not mean the best-fit straight line. | |

## Random error is a fluctuating error often present in experiments. It is linked to precision: imprecise data => "high" random error; precise data => "low" random error. Repeated measurements do reduce random errors. Sources of random errors can include varying reading/human error and other randomly flucuating factors which cannot be controlled during experiments. | |

## Scalar multiplication of vectors, changes the magnitude of the vector but not the direction. For scalar $$a$$ and vector $$\vec{A}$$ with x- or horizontal component $$A_H=A \cos \theta$$ y- or vertical compnonet $$A_V= A \sin \theta$$ magnitude $$A=\sqrt{A_H^2 + A_V^2}$$ The multiplication $$a \times \vec{A}$$ has magnitude $$a \times A$$. The division $$\vec{A} \div a$$ has magnitude $$A \div a$$. | |

## Scalar quantities have magnitude only. Direction or changes in direction have no effect on scalar quantities. Examples include distance, speed, mass and temperature. | |

## Signifiant figuresa rule, the number of significant digits in a result should not exceed that of the least precise value upon which it depends. | |