Die Druckversion wird nicht mehr unterstützt und kann Darstellungsfehler aufweisen. Bitte aktualisiere deine Browser-Lesezeichen und verwende stattdessen die Standard-Druckfunktion des Browsers.

Measurement, Units, and Uncertainty

Introduction

Every scientific measurement answers two questions: How much? and in what unit? A complete measurement also tells the reader how confidently the value is known. This course is designed for Grades 9–10. You will learn how to choose and use units, read measuring instruments, convert quantities, report significant figures, estimate uncertainty, distinguish accuracy from precision, and communicate experimental results responsibly.

These skills connect Physics, Chemistry, Mathematics, Engineering, and everyday decision-making. They matter whenever you time a race, determine the density of a material, compare temperatures, measure medicine, manufacture a machine part, or judge whether two experimental results agree.

The seven symbols in the image represent the SI base units. The International System of Units is the modern internationally agreed measurement system used across science and technology.

The video above introduces metric unit conversion. As you watch, focus on why multiplying by a conversion factor can change the unit without changing the physical quantity.

Learning Goals

By the end of this course, you should be able to:

Measurement: Explain why a measured value needs both a numerical value and a unit.
International System of Units: Use common SI base units, derived units, and prefixes correctly.
Dimensional analysis: Convert between compatible units using conversion factors.
Measuring instrument: Choose an instrument with suitable range and resolution and read it correctly.
Accuracy and precision: Distinguish accuracy, precision, random variation, and systematic effects.
Measurement uncertainty: Express a result using an estimated uncertainty and calculate relative or percentage uncertainty.
Significant figures: Report values with a number of digits justified by the measurement.
Propagation of uncertainty: Apply simple school-level rules for combining uncertainties in calculated quantities.
Experimental data: Use repeated measurements, averages, and spread to support a scientific conclusion.

What Is a Measurement?

A physical quantity is a property that can be measured, such as length, mass, time, temperature, electric current, or speed. A measurement compares that quantity with an agreed reference. The result is written as a number and a unit, for example 1.42 m, 68.3 g, or 12.5 s.

A number without a unit is often incomplete. Saying that a table is "1.2 long" does not communicate whether the length is 1.2 metres, 1.2 centimetres, or 1.2 kilometres. Units make measurements interpretable and comparable.

Measurements are never infinitely exact. Every measuring process has limitations caused by instrument resolution, calibration, the measurement method, environmental conditions, and variation in the quantity being measured. This is why a scientifically useful result often has the form:

measured value ± uncertainty

For example, a length reported as 12.4 ± 0.1 cm communicates more than the statement "the length is 12.4 cm." The uncertainty describes the reasonable doubt associated with the measurement; it is not simply a confession that somebody made a mistake.

Measurand, Value, and Unit

The measurand is the quantity you intend to measure. If you measure the diameter of a coin, the diameter is the measurand. Your instrument produces an indication from which you obtain a measured value.

Before measuring, ask yourself:

Measurand: What exactly am I trying to determine?
Measurement unit: Which unit is appropriate?
Measuring instrument: Which tool has a suitable range and resolution?
Measurement method: How will I reduce avoidable bias and variation?
Measurement uncertainty: What limits the reliability of the result?

The International System of Units

The International System of Units, abbreviated SI, is the modern metric system. It provides seven base units. Other SI units can be derived from combinations of these base units.

Base quantity	SI base unit	Symbol	Example
Time	second	s	Reaction time
Length	metre	m	Height of a doorway
Mass	kilogram	kg	Mass of a backpack
Electric current	ampere	A	Current in a circuit
Thermodynamic temperature	kelvin	K	Temperature in physical science
Amount of substance	mole	mol	Amount of particles in chemistry
Luminous intensity	candela	cd	Intensity of a light source

In school science you will also often use accepted units such as degrees Celsius for temperature and litres for volume. When you calculate with units, keep the quantity and its unit together.

Derived Units

A derived unit is formed from base units. For example:

Speed: metre per second, written m/s.
Area: square metre, written m².
Volume: cubic metre, written m³.
Density: kilogram per cubic metre, written kg/m³.
Force: newton, written N, where one newton is equivalent to kg·m/s².
Energy: joule, written J.
Power: watt, written W.

Units can help you check an equation. If a formula for speed does not end with a length unit divided by a time unit, something is probably wrong.

SI Prefixes

Prefixes scale units by powers of ten. They make very large and very small quantities easier to write.

Prefix	Symbol	Factor	Example
kilo	k	10³	1 km = 1000 m
centi	c	10⁻²	1 cm = 0.01 m
milli	m	10⁻³	1 mm = 0.001 m
micro	µ	10⁻⁶	1 µm = 0.000001 m
nano	n	10⁻⁹	1 nm = 0.000000001 m

Uppercase and lowercase symbols matter. For example, m can mean metre when it is a unit symbol, while the prefix m means milli when attached to another unit. The prefix M means mega. Correct symbol writing prevents serious misunderstandings.

Converting Units with Dimensional Analysis

A conversion factor is a ratio equal to one. Because 1 km = 1000 m, both 1000 m / 1 km and 1 km / 1000 m represent the same physical equivalence.

Suppose a running track is 2.50 km long:

2.50 km × 1000 m / 1 km = 2500 m

The kilometre unit cancels, leaving metres. This method is called dimensional analysis or the factor-label method.

For squared and cubed units, the conversion factor must also be squared or cubed. Since 1 cm = 0.01 m:

1 cm² = 0.0001 m²

and

1 cm³ = 0.000001 m³

A common mistake is to convert only the number but not the power of the unit. Always treat the unit as part of the mathematics.

A Conversion Strategy

Given quantity: Write the value with its current unit.
Target unit: Decide which unit you need.
Conversion factor: Choose a factor that places the unwanted unit so that it cancels.
Calculation: Multiply the numerical values.
Unit check: Confirm that only the target unit remains.
Reasonableness check: Ask whether the size of the answer makes sense.

Measuring Instruments and Resolution

Different instruments are designed for different ranges and levels of detail. A metre rule may be suitable for a desk, while a vernier caliper can measure a small diameter more precisely.

Resolution is the smallest change in a quantity that an instrument can display or distinguish. A ruler marked every millimetre has a finer resolution than one marked only every centimetre.

A vernier caliper combines a main scale with a sliding vernier scale. It can measure outside dimensions, inside dimensions, and depth.

For an analogue scale, a common school-laboratory convention is to estimate the reading uncertainty as about half the smallest scale division when the scale can be read clearly. For a digital instrument, a simple school estimate is often one unit of the last displayed digit unless the manufacturer gives a more appropriate specification. These are introductory conventions, not universal metrology rules.

Reading a Scale Correctly

When you read an analogue instrument:

Parallax: Place your eye perpendicular to the scale to reduce viewing-angle error.
Zero error: Check whether the instrument reads zero when it should.
Range: Make sure the expected value lies within the instrument's working range.
Resolution: Identify the smallest marked division before recording data.
Units: Record the unit with every measured value.

When measuring liquid volume in a graduated cylinder, place the cylinder on a level surface and read the appropriate point of the meniscus at eye level. For water and many other liquids in glass, this is normally the bottom of the concave meniscus.

Accuracy, Precision, Error, and Uncertainty

In ordinary school science, accuracy describes how close a result is to an accepted or reference value, while precision describes how closely repeated measurements agree with one another. These ideas are related but not identical.

A set of measurements can be precise but inaccurate. For example, a miscalibrated balance might repeatedly give almost the same mass while every result is shifted by 2 g. The repeated values are tightly grouped, but the instrument has a systematic bias.

Measurement error is the difference between a measured value and a reference value when such a reference is available. Measurement uncertainty describes the doubt or range of plausible values associated with the measurement result. Error and uncertainty are therefore not synonyms.

Random and Systematic Effects

Random variation causes repeated measurements to scatter. Examples include small changes in reaction time, estimating between scale marks, or fluctuating sensor readings. Repeating measurements can help you characterize this variation.

Systematic effects tend to shift results in a consistent direction. Examples include a zero offset, a stretched ruler, a temperature sensor that is incorrectly calibrated, or a method that consistently measures from the wrong reference point.

Repeating a measurement many times does not automatically remove a systematic effect. Instead, you should identify its cause, improve the method, calibrate the instrument, apply a justified correction, or include the effect in the uncertainty evaluation.

Repeated Measurements

Repeated measurements give you evidence about variation. Suppose you measure the period of a pendulum five times and obtain 1.42 s, 1.39 s, 1.44 s, 1.41 s, and 1.40 s.

The arithmetic mean is:

mean = sum of measurements / number of measurements

For these values, the mean is 1.412 s. At this level, you might report 1.41 s after rounding appropriately.

The range is the maximum value minus the minimum value. Here the range is 1.44 s − 1.39 s = 0.05 s. A simple classroom estimate of scatter is sometimes half the range, but this is not the same as the formal statistical standard uncertainty used in professional metrology.

With many repeated observations influenced by numerous small random effects, data may form an approximately bell-shaped distribution. This is a useful model, but you should not assume every dataset is normally distributed just because it contains repeated measurements.

Expressing Uncertainty

An uncertainty should be expressed with the same unit as the measured quantity. A useful form is:

x = measured value ± absolute uncertainty

For example:

L = 25.4 ± 0.2 cm

This states a best estimate of 25.4 cm and an absolute uncertainty of 0.2 cm.

The relative uncertainty compares the uncertainty with the size of the measurement:

relative uncertainty = absolute uncertainty / measured value

The percentage uncertainty is:

percentage uncertainty = relative uncertainty × 100%

For 25.4 ± 0.2 cm:

percentage uncertainty = 0.2 / 25.4 × 100% ≈ 0.79%

Percentage uncertainty is useful when comparing the quality of measurements of different sizes.

The video above focuses on significant figures and uncertainty in measured quantities. Compare its reporting choices with the rules used in your own science course.

Reporting Uncertainty Sensibly

Do not report more digits than your measurement can support. A common school-science practice is to round the uncertainty to one significant figure, or sometimes two significant figures when the first digit is 1 or 2, and then round the measured value to the same decimal place.

For example, instead of writing:

12.4376 ± 0.0831 cm

a more realistic report might be:

12.44 ± 0.08 cm

The exact convention can vary by curriculum or laboratory, so always follow the method your course requires.

Significant Figures

Significant figures communicate which digits in a measured value are meaningful at the stated precision.

Useful rules include:

Nonzero digit: Every nonzero digit is significant.
Interior zero: Zeros between nonzero digits are significant.
Leading zero: Zeros used only to locate the decimal point are not significant.
Trailing zero: Trailing zeros to the right of a decimal point are significant when they communicate measured precision.
Scientific notation: Scientific notation can make the intended number of significant figures clear.

Examples:

0.00450 has three significant figures.

2.030 has four significant figures.

1.20 × 10³ has three significant figures.

The first video introduces significant figures; the second provides a faster review including rounding rules. Use them to compare examples and identify where calculators can display more digits than an experiment actually justifies.

Significant Figures in Calculations

For multiplication and division, a common introductory rule is to round the final answer to the same number of significant figures as the least precise measured input.

For addition and subtraction, the limiting factor is usually the decimal place rather than the total number of significant figures. The result should normally be rounded to the least precise decimal place among the measured inputs.

Keep extra digits during intermediate steps and round once at the end. Early rounding can increase numerical error.

Combining Uncertainties in Calculations

For Grades 9–10, this course uses simple worst-case rules that are easy to apply. More advanced science often combines independent standard uncertainties using statistical methods such as root-sum-square calculations.

For a sum or difference:

absolute uncertainties add

If A = 5.0 ± 0.2 cm and B = 3.0 ± 0.1 cm, then:

A + B = 8.0 ± 0.3 cm

For multiplication or division:

relative or percentage uncertainties add

If a rectangle has length 10.0 ± 0.1 cm and width 5.0 ± 0.1 cm, the percentage uncertainties are 1% and 2%. The area is 50.0 cm² with an estimated percentage uncertainty of about 3%, giving an absolute uncertainty of about 1.5 cm².

For a power such as y = x², a simple worst-case rule gives approximately twice the relative uncertainty of x. Use this only when your course expects this approximation.

Planning a Reliable Investigation

Good measurement begins before data collection. A strong experimental plan states the measurand, selects suitable equipment, controls important variables, describes how readings will be taken, and explains how uncertainty will be estimated.

A useful planning sequence is:

Research question: Write a measurable question.
Variable: Identify independent, dependent, and control variables where appropriate.
Instrument selection: Choose instruments with suitable range and resolution.
Calibration: Check zero points and known references when possible.
Repeated measurement: Decide how many repeats are useful and feasible.
Data table: Prepare headings with units before collecting values.
Uncertainty analysis: Decide how uncertainty will be estimated and propagated.
Conclusion: Compare the size of the observed effect with the uncertainty before claiming a relationship.

A difference between two measurements is not automatically meaningful. If the uncertainty intervals overlap strongly, your evidence may not support a clear distinction.

Worked Example: Density of a Metal Block

Suppose you measure a rectangular metal block.

Mass: m = 125.4 ± 0.1 g

Length: l = 5.00 ± 0.05 cm

Width: w = 2.00 ± 0.05 cm

Height: h = 1.00 ± 0.05 cm

The volume is:

V = l × w × h = 10.0 cm³

Using the simple worst-case rule, the percentage uncertainty in volume is approximately:

1% + 2.5% + 5% = 8.5%

The density is:

density = mass / volume = 12.54 g/cm³

The mass uncertainty is about 0.08%, so the total percentage uncertainty in density is approximately 8.6%. The absolute uncertainty is about:

12.54 × 0.086 ≈ 1.1 g/cm³

A sensible school-level report is therefore approximately:

density = 12.5 ± 1.1 g/cm³

Notice that the uncertainty is dominated by the least precise dimension, the height. Improving the height measurement would probably improve the final density more than using a balance with even finer resolution.

Common Mistakes and How to Fix Them

Missing unit: Always attach the correct unit to measured values and calculated results.
False precision: Do not copy every calculator digit into the final answer.
Wrong prefix factor: Write the conversion factor explicitly so units cancel.
Parallax error: Read analogue scales at eye level and perpendicular to the scale.
Ignoring zero offset: Check whether an instrument gives a nonzero reading when the true input should be zero.
One measurement only: Repeat measurements when random variation is important.
Confusing accuracy and precision: Remember that tightly grouped values can still be shifted away from a reference value.
Treating uncertainty as failure: Uncertainty is a normal part of measurement and should be communicated, not hidden.

Interactive Tasks

Quiz: Test Your Knowledge

What is the SI base unit of length? (metre) (!centimetre) (!kilometre) (!litre)

Which prefix represents a factor of one thousandth? (milli) (!kilo) (!centi) (!mega)

What is 2.50 kilometres expressed in metres? (2500 metres) (!250 metres) (!25 metres) (!25000 metres)

Using the common school convention, what uncertainty is reasonable for an analogue scale with one millimetre divisions? (half a millimetre) (!five millimetres) (!ten millimetres) (!one centimetre)

What does precision describe in repeated measurements? (how closely repeated results agree) (!how close a result is to zero) (!how large the unit is) (!how many instruments are available)

Which situation is most clearly a systematic effect? (a balance always reads two grams too high) (!reaction times vary from trial to trial) (!a sensor fluctuates randomly around a stable value) (!repeated ruler estimates differ slightly)

A length is reported as 12.4 centimetres with an uncertainty of 0.2 centimetres. What is its approximate percentage uncertainty? (1.6 percent) (!0.2 percent) (!6.2 percent) (!16 percent)

How many significant figures are in 0.00450? (three) (!one) (!two) (!five)

Using the simple worst-case rule, what is 3.2 plus or minus 0.1 centimetres added to 5.0 plus or minus 0.2 centimetres? (8.2 plus or minus 0.3 centimetres) (!8.2 plus or minus 0.1 centimetres) (!8.0 plus or minus 0.2 centimetres) (!8.3 plus or minus 0.2 centimetres)

Which SI derived unit is suitable for speed? (metres per second) (!kilograms per metre) (!seconds per kilogram) (!metres squared)

Memory Game

Resolution	Smallest change an instrument can display or distinguish
Accuracy	Closeness of a result to an accepted or reference value
Precision	Closeness of repeated measurements to one another
Uncertainty	Quantified doubt associated with a measurement result
Calibration	Comparison or adjustment using a known reference
Meniscus	Curved liquid surface read in a measuring cylinder
Prefix	Symbol or name that scales a unit by a power of ten

Drag and Drop

Match the correct terms.	Topic
one thousand times a base unit	kilo
one hundredth of a base unit	centi
one thousandth of a base unit	milli
spread caused by unpredictable trial-to-trial changes	random variation
consistent shift caused by a measurement method or instrument	systematic effect

...

Crossword Puzzle

Metre	What is the SI base unit of length?
Kilogram	What is the SI base unit of mass?
Precision	What word describes close agreement among repeated measurements?
Meniscus	What curved liquid surface is read in a graduated cylinder?
Systematic	What type of effect can shift repeated results in one consistent direction?
Uncertainty	What term describes quantified doubt in a measurement result?

LearningApps

Cloze Text

A scientific measurement combines a numerical value with a

. The internationally agreed modern metric system is called the

. An instrument's smallest distinguishable change is its

. Measurements that cluster closely together show high

. Closeness to an accepted reference value is called

. A consistent shift in one direction can result from a

effect. Unpredictable trial-to-trial spread is associated with

variation. The quantified doubt stated with a measurement is its

. Dividing absolute uncertainty by the measured value gives

uncertainty. Digits that communicate justified measurement precision are called

figures.

Open-Ended Tasks

Easy

Measurement audit: Measure five classroom objects with a ruler or tape, record each value with a unit, state the instrument resolution, and explain one limitation for every measurement.
Unit conversion poster: Create a one-page visual guide that teaches conversions among kilometres, metres, centimetres, millimetres, and micrometres using powers of ten and at least four worked examples.
Instrument resolution hunt: Photograph or sketch four measuring instruments, identify their ranges and resolutions, and decide which instrument would best measure a coin diameter, a classroom length, a liquid volume, and a short time interval.
Accuracy and precision sketch: Produce your own four-panel target-style diagram showing high and low accuracy and precision, then write one sentence explaining each panel.

Standard

Pendulum timing investigation: Time ten oscillations of a simple pendulum in at least five trials, calculate a mean period, describe the spread, estimate an uncertainty, and explain how timing more than one oscillation changes relative uncertainty.
Density experiment: Determine the density of a regular solid from measured mass and dimensions, report each measurement with uncertainty, propagate uncertainties using the simple worst-case rules, and identify which measurement limits the final result.
Calibration interview: Interview a laboratory technician, science teacher, engineer, craftsperson, or technician about how they check measuring tools, then summarize two examples of calibration and one consequence of poor calibration.
Measurement tutorial video: Produce a two- to four-minute video that demonstrates correct reading of a ruler, graduated cylinder, or caliper and explicitly explains parallax, resolution, units, and uncertainty.

Advanced

Uncertainty propagation project: Design a calculation that uses at least three measured inputs, compare the result obtained with and without uncertainty propagation, and explain why the uncertainty changes the strength of your conclusion.
Systematic error investigation: Create an experiment in which you deliberately introduce a known zero offset or scale error, compare corrected and uncorrected results, and explain why repeated trials alone do not remove the bias.
Data distribution study: Collect at least thirty repeated measurements of a quantity such as reaction time or drop time, create a histogram, calculate a mean and range, describe the shape of the distribution, and discuss whether any values should be investigated as possible outliers.
Metrology field visit: Visit or virtually investigate a laboratory, workshop, manufacturing site, pharmacy, weather station, or quality-control facility and produce a report showing how measurement traceability, calibration, and uncertainty influence real decisions.

Learning Assessment

Experimental design assessment: Plan an investigation to compare two methods of measuring the same quantity, justify your instrument choices, predict important uncertainty sources, and explain how you would decide whether the methods agree.
Uncertainty comparison assessment: Compare two measurements with different absolute uncertainties and determine which has the smaller percentage uncertainty; explain why absolute uncertainty alone can be misleading.
Error diagnosis assessment: Analyze a dataset that is tightly clustered but far from a reference value, identify the likely measurement problem, and propose a method to test your explanation.
Unit reasoning assessment: Derive the unit of a calculated quantity from its formula and use dimensional reasoning to identify one deliberately incorrect equation.
Reporting assessment: Rewrite an over-precise calculator result as a scientifically justified measurement, including unit, uncertainty, and appropriate significant figures, and explain each rounding choice.
Transfer assessment: Choose a real-world context such as medicine, sport, construction, climate monitoring, or manufacturing and explain how an underestimated measurement uncertainty could lead to a poor decision.

Evidence of Learning

Knowledge: You can explain SI base and derived units, common prefixes, instrument resolution, significant figures, accuracy, precision, random variation, systematic effects, and measurement uncertainty.

Skills: You can convert units, read measuring instruments, estimate school-level uncertainties, calculate relative and percentage uncertainty, use repeated measurements, propagate simple worst-case uncertainties, and evaluate whether a result is reported with justified precision.

Products: Strong evidence may include a clearly labelled data table, an uncertainty-aware laboratory report, a unit-conversion resource, an instrument demonstration, a graph of repeated measurements, or a short explanatory video.

Reasoning: You can identify which source of uncertainty dominates a calculation, distinguish random spread from systematic bias, and decide whether the evidence is strong enough to support a claimed difference or relationship.

Transfer: You can apply measurement thinking beyond the classroom to evaluate specifications, tolerances, quality control, health data, environmental measurements, engineering designs, and everyday quantitative claims.

OERs on the Topic

For additional reliable learning resources, explore the International System of Units, Significant figures, Accuracy and precision, and Metrology articles. You can also use the official SI resources from the Bureau International des Poids et Mesures and the National Institute of Standards and Technology: