Notes: Understanding the concepts of Accuracy, Reliability, and Validity
in practical investigations
1. Accuracy (Is the result correct?)
An experiment is accurate if its results or measurements are very close to the
actual or real outcome
Example 1 - Human Error:
A student is measuring the volume of water in a beaker. He reads the
measurement from the top instead of at eye level, which makes the result
incorrect.
To be more accurate, he should read the measurement at eye level.

Example 2 - Instrumental Error:
A student uses a scale to measure the mass of a beaker, but the scale is broken and it
reads 2mg even with nothing on it. This is an instrumental error. To be more accurate,
the student should use a new scale or subtract 2.00mg from all their measurements.
Anomalous Data
Anomalous data, also known as an outlier, is a data point that is significantly
different from the other data points in a set.
Example:
A student investigated the effect of temperature on the time taken for the enzyme
amylase to digest starch.
The image below shows a graph with a clear anomalous point that does not follow the
general trend of the other plotted points.
Anomalous data can be caused by mistakes in the experiment, such as a human
error or an instrumental error.
2. Reliability (Can you trust the results?)
Reliability means you get the same result every time you do the same test.
Example:
A student is testing how temperature affects a chemical reaction. They do the test with
the same temperature three times and get the following results:
-
Test 1: Reaction time of 15 seconds
Test 2: Reaction time of 16 seconds
Test 3: Reaction time of 15.5 seconds
These results are very close. This means the data is reliable.

How to increase or improve reliability of the experiment?
To improve reliability, the student should repeat the experiment (at least three times)
and be more careful with the measurements.
3. Validity (Is it a fair test?)
What it is: Validity means the experiment is a fair test.
A valid experiment only changes one thing (= independent variable) to see what
happens, while keeping everything else the same.
Example: A student is testing if the volume of water affects plant growth.
o

A valid experiment would be one where the student uses the same type of
plant, the same amount of light, and the same type of soil for all the plants.
The only thing they change is the volume of water each plant gets.
How to be more valid: You must control all the other variables and keep them
the same. For example, keep the amount of water and sunlight the same for all
your plants.