Method and Sources of Error

Navigate the knowledge tree: 🌿 Biology ➡ NCEA Level 2 Biology ➡ 2.1 Investigation ➡ Lesson 4-5: Method and Sources of Error

Learning Intentions

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

Write a detailed step-by-step method that is valid and repeatable.
Choose equipment that suits the investigation.
Recognise possible sources of error in an investigation and explain how they could affect results.
Suggest practical ways to reduce sources of error and improve the method.

Glossary

Key terms and definitions.

accuracy: How close a result is to the true or correct value.

bias: A consistent influence that causes results to lean in one direction. Oten leads to systematic error.

calibrate: To check and adjust equipment so it gives correct measurements.

error: Anything that affects the accuracy or reliability of results. They are not mistakes and cannot be fully avoided.

fair test: An investigation where only the independent variable is changed and all other variables are controlled.

mean: The total of all results divided by the number of results. Its use in data analysis helps reduce the effect of random error.

method: A step-by-step description of how an investigation is carried out so it can be repeated.

parallax error: A type of systematic error where a measurement is read from the wrong angle instead of at eye level.

precision: How close repeated measurements are to each other. Related to reliability, not accuracy.

random error: Unpredictable variation in results caused by chance. It affects reliability.

reliability: How consistent results are when an investigation is repeated.

systematic error: An error that causes results to be consistently too high or too low. It affects accuracy.

validity: How well an investigation tests the hypothesis. Are measurements measuring what they’re supposed to measure? Does the method test what it’s supposed to test?

zero error: A type of systematic error where equipment does not read zero when it should.

How to write a valid, repeatable method

A good scientific method explains exactly what was done, in the correct order, using clear, specific language - so if another student followed your method, they should get similar results. It must be:

Valid, meaning it actually tests the hypothesis and produces valid results
Written in clear, numbered steps
In the correct order
Detailed enough in what equipment is used and how control variables are kept the same (i.e. it is a fair test).
Detailed with specific quantities, units and times
Written in past tense and passive voice

How to choose the right equipment

The equipment you choose must be suitable for the variable being measured; it must be accurate enough to measure what you are intending to meausure. When choosing equipment ask yourself the following questions:

Does this piece of equipment match the scale of measurement?
Is this piece of equipment appropriate for the substance we are handling?
Will this piece of equipment allow me to take consistent measurements?

The following equipment are suitable for the osmosis investigation:

What are the sources of error?

A source of error is anything that could affect the accuracy or reliability of results. Errors are not mistakes — they are unavoidable parts of carrying out investigations in Science.

There are two main types of error: systematic error and random error.

Systematic errors

Systematic errors cause results to be consistently too high or too low. They affect accuracy, not reliability. The most common causes of systematic error are:

Miscalibrated equipment
e.g. the balance was not zeroed (zero error)
e.g. a thermometer reading 2°C too high
e.g. using a ruler with a broken zero mark (zero error)
Consistent measuring bias
e.g. reading the meniscus incorrectly (parallax error)
e.g. reading the meter needle from the wrong angle (parallax error)
e.g. using a stretched measuring tape that sags/bends
e.g. getting the colours wrong when looking at a pH scale
Faulty method design
Environmental conditions affecting all samples.
e.g. air conditioning on when taking temperature readings

As a result of systematic errors, results may:

Appear consistent, but are in fact not the true value (are wrong).
Create trends that look valid (true) but are inaccurate.

Random errors

Random errors cause results to vary unpredictably between repeats. This lowered precision affects reliability, not accuracy. The most common causes of random errors are:

Human reaction times
e.g. dropping two balls at slightly different times when they're meant to be dropped a the same time.
e.g. inconsistent timing when using a stopwatch
Slight differences between samples
e.g. two paper planes made slightly differently when they're meant to be exactly the same
Small environmental changes
e.g. weather conditions such as temperature and humidity
Natural biological variation
e.g. two potatoes having slightly different water content
e.g. different leaf thickness in photosynthesis experiments

As a result of systematic errors, results may:

Be scattered with the pattern much harder to see.
Have means that are still accurate, but the data is less reliable.

How to improve the validity and reliability of the results

A valid method tries to reduce and manage errors as much as possible. There are some general tips you can follow to reduce systematic error and improve validity of your results, and reduce random error to improve the reliability of your results.

Reduce systematic error, improve validity

Calibrate equipment before use
Use the same equipment throughout the investigation
Check zero points and scales
Keep control variables constant

Reduce random error, improve reliability

Repeat measurements
Use large sample sizes
Calculate means
Follow a consistent measuring technique

For the osmosis investigation, these are the specific errors you must consider:

More on Method and Sources of Error

📕 article 📸 image 🎮 interactive 🎦 video