Fundamental Data Analysis

What Fundamental Data Analysis covers

Fundamental Data Analysis is examined in all three written papers — the specification states that Components 01, 02 and 03 each assess content from across all the teaching modules, so nothing is confined to one paper. It covers factors affecting accuracy and uncertainty, units, prefixes, standard form and angles, the language of measurement, Distributions, dot-plots and graphical displays, calculating and combining uncertainties and estimating magnitudes of everyday quantities.

The 6 subtopics

Each one has its own page.

• Factors affecting accuracy and uncertaintyRecall questions on the resolution floor of a single reading, poorly defined quantities, fluctuating displays, random against systematic contributions, calibration and response time, and finding which source of uncertainty dominates.Open →
• Units, prefixes, standard form and anglesRecall questions on defining and converting radians, arc length, a calculator left in the wrong angle mode, the prefixes from pico to giga, and arithmetic in standard form.Open →
• The language of measurementRecall questions on accuracy, precision and resolution and how they differ, sensitivity, response time, uncertainty, systematic and zero errors, which errors averaging reduces, an instrument that is sensitive but not accurate, why a large thermometer bulb responds slowly, and a drifting balance.Open →
• Distributions, dot-plots and graphical displaysRecall questions on reading a mean and its spread from a dot-plot, when a median is better, recognising and handling an outlier, scatter and pie charts, logarithmic scales, and uncertainty bars.Open →
• Calculating and combining uncertaintiesRecall questions on absolute against percentage uncertainty, combining them through sums, products and powers, why subtracting similar values is costly, uncertainty in a gradient or intercept, and quoting an uncertainty.Open →
• Estimating magnitudes of everyday quantitiesRecall questions on order of magnitude estimates and their uses, estimating the mass of an apple and a person, the volume of a laboratory, the thickness of paper, a kettle's power and heating time, walking speed and a lifetime of heartbeats, the densities of air and water, the diameter of an atom, and spotting an implausible answer.Open →

What you need to know

Answer each one before you reveal it.

Take Fundamental Data Analysis further

The same content, four other ways.

Commonly confused

Pairs that lose marks when they are blurred together.

• Resolution vs Sensitivity

  Resolution: the smallest change in the measured quantity that produces a perceptible change in the reading. Sensitivity: The change in output produced per unit change in the input quantity, which is the gradient of the calibration graph.

• Absolute uncertainty vs Percentage uncertainty

  Absolute uncertainty: the uncertainty quoted in the unit of the measurement itself, and the form that is added when two quantities are added or subtracted. Percentage uncertainty: The uncertainty expressed as a fraction of the measurement and multiplied by a hundred, and the form that is added when quantities are multiplied or divided.

• Mean vs Median

  Mean: the sum of all the readings divided by how many there are, so a single extreme value drags it towards itself. Median: The middle reading once they are placed in order, which an extreme value barely shifts.

Questions from this topic

Each one with the model answer underneath.

1. 1

   Which factors affect the uncertainty of a measurement?

   Model answer

   The resolution of the instrument, how well the quantity itself is defined and how steady it is, and the calibration and technique with which the instrument is used.

2. 2

   How does the resolution of an instrument set a floor on the uncertainty of a single reading?

   Model answer

   No change smaller than one division or one displayed digit can be detected, so the reading can never be known more closely than that however carefully it is taken.

3. 3

   Give an example of a quantity that is poorly defined and explain why that adds uncertainty.

   Model answer

   The diameter of a slightly oval wire has no single value, so different readings differ genuinely rather than because of any fault in the micrometer.

4. 4

   A meter reading fluctuates in its last two digits. How should the uncertainty be judged?

   Model answer

   The uncertainty is taken from the range over which the reading fluctuates, since that spread is larger than the resolution of the display.

5. 5

   Distinguish the two kinds of contribution to the difference between a measurement and the true value.

   Model answer

   Random contributions scatter readings either side of the true value and are reduced by averaging repeats, while systematic contributions shift every reading the same way and are not.

6. 6

   How can the surroundings affect the uncertainty of a laboratory measurement?

   Model answer

   Draughts and temperature drift change the quantity being measured during the experiment, and stray light or background radiation adds a signal the detector cannot distinguish from the one being measured.

What is inside Levo

Six ways to work the same material.

Fundamental Data Analysis revision questions

What does Fundamental Data Analysis cover in OCR A-Level Physics B?

6 subtopics: factors affecting accuracy and uncertainty, units, prefixes, standard form and angles, the language of measurement, distributions, dot-plots and graphical displays, calculating and combining uncertainties and estimating magnitudes of everyday quantities. Each one has its own page with questions and model answers.

How is Fundamental Data Analysis organised?

By the OCR H557 specification, subtopic by subtopic, so it matches the order you are taught it in.