# Working Scientifically in Biology

> Questions, hypotheses, variables, fair tests, validity, reliability and accuracy, data, depth studies and working with First Nations knowledge.

From HSC Biology on WhizzNotes, free study notes for NSW students: https://whizznotes.com/biology/working-scientifically/. Updated 3 November 2026.
Year 11 and Year 12 boxes go deeper than the Year 10 text around them.

### Story time: Why do the tadpoles keep dying?
Mia's class keeps tadpoles in a tank for a science project. Every few weeks some die. One student blames the tap water. Another blames the sun on the window. A third says they are just unlucky.

Mia does not guess. She sets up six small tanks. Three get tap water left out for two days, and three get fresh tap water straight from the tap. Same food, same shade, same number of tadpoles. After three weeks, the fresh tap water tanks have lost far more tadpoles.

Now she has **evidence**, not an opinion. Changing one thing, keeping the rest the same and repeating the test is how biologists find out what is really going on.

**In short:** Working scientifically in biology means testing a question fairly: write a hypothesis (if, then, because), change one independent variable, measure the dependent variable and control everything else. Repeat trials and use the mean, so the results are valid, reliable and accurate.

## Starting point: what you already know

- Independent, dependent and controlled variables from Years 7 to 10 science.
- Drawing tables and line or column graphs.
- Calculating a mean (average): add the values and divide by how many there are.

## From question to hypothesis

Every investigation starts with a **question** that can be tested, like "Does the amount of light change how fast pondweed makes oxygen?"

A **hypothesis** is a testable prediction with a reason. A good one names both variables:

> If light intensity increases, then the rate of oxygen production will increase, because light provides the energy for photosynthesis.

## Variables

| Variable | Meaning | Pondweed example |
|---|---|---|
| Independent | The one thing **you change** | Distance of the lamp |
| Dependent | The thing **you measure** | Bubbles of oxygen per minute |
| Controlled | Things **kept the same** | Water temperature, type and size of plant, time |

A **control group** (or control) is a set-up where the independent variable is not applied, so you have something to compare with. In Mia's story, the tanks with water left to stand are compared with the fresh tap water tanks.

### Key idea: Validity, reliability and accuracy
- **Valid**: the test measures what it claims to measure, because only one variable was changed and the rest were controlled.
- **Reliable**: repeating the test gives similar results. Repeat each trial at least 3 times and use the mean.
- **Accurate**: the result is close to the true value. Good equipment and careful methods improve accuracy.

### Watch out: Reliable is not the same as accurate
A scale that always reads 2 g too heavy gives **reliable** (repeatable) results that are **not accurate**. This is a **systematic error**. Random errors, like reading a ruler from a slightly different angle each time, are reduced by repeating and averaging.

## Safe and ethical work

Before any practical, write a **risk assessment**: the hazard, the risk, and how you will lower it. Biology adds two special areas.

- **Living things.** Animal research in schools must follow animal ethics rules. Cause the least harm, use the fewest animals and replace animals with models or plants where possible.
- **Microbes.** Treat every culture as if it could cause disease. Seal agar plates with tape, never open them after incubating and incubate at 25 to 30 degrees, not body temperature.

## Showing your data

| Type of data | Best graph |
|---|---|
| Both variables are numbers that change smoothly (temperature and enzyme activity) | Line graph |
| The independent variable is a category (type of fertiliser) | Column graph |
| Parts of a whole (percentage of each blood type) | Pie chart or divided bar |
| Looking for a link between two measured things (height and arm span) | Scatter plot |

Put the independent variable on the horizontal axis, label both axes with units and give the graph a title.

### Worked example: Finding the mean
Bubbles per minute in three trials: 18, 21 and 20.
$$\text{mean} = \frac{18 + 21 + 20}{3} = \frac{59}{3} \approx 19.7 \text{ bubbles per minute}$$
If one trial had given 45, that would be an **outlier**. Check it, and repeat that trial rather than averaging it in without thinking.

## First Nations knowledge and science

Aboriginal and Torres Strait Islander peoples have studied Australian plants, animals, seasons and fire for more than 60 000 years. This knowledge was built by careful observation over many generations, which is also what science does.

This knowledge belongs to the communities who hold it. It is called **Indigenous Cultural and Intellectual Property (ICIP)**. When you use it in a project, you should

- use sources that the community has shared publicly or approved,
- name the community or Nation the knowledge comes from,
- ask permission from the right people before using knowledge that is not public, and
- never claim it as your own idea.

**Mind map**

```text
Working scientifically
  Plan
    Testable question
    Hypothesis: if, then, because
    Risk assessment and ethics
  Variables
    Independent: change
    Dependent: measure
    Controlled: keep the same
  Quality
    Valid: fair test
    Reliable: repeat
    Accurate: close to true
  Data
    Tables and means
    Line, column, scatter
    Outliers and errors
  Respect
    First Nations knowledge
    ICIP protocols
```

### Year 11: Depth studies and secondary sources
In Year 11 and 12 you complete **depth studies**: long tasks where you investigate one question in detail. A depth study can be a first-hand practical, a fieldwork report, a data analysis, a review of secondary sources, or a model.

When you use **secondary sources** (articles, data sets, websites), judge them:

- **Who** wrote it? Are they an expert, and do they gain from the result?
- **When**? Is it recent enough?
- Is it **peer reviewed** (checked by other scientists before publishing)?
- Does it agree with other good sources?

Always reference your sources so others can check them.

### Year 12: Analysing data like an HSC examiner
HSC questions often give you a graph and ask you to **analyse** it. A strong answer

1. describes the **trend** with numbers from the graph ("as temperature rose from 20 to 40 degrees, activity rose from 10 to 45 units"),
2. points out any **change in trend** or **anomaly**,
3. **explains** the trend using biology, and
4. comments on **limits** of the data, such as sample size or missing controls.

Remember that **correlation is not causation**. Two things rising together does not prove one causes the other. A third factor may cause both.

## Quick summary

- Start with a testable question, then write a hypothesis with "if, then, because".
- Change one independent variable, measure the dependent variable and control everything else.
- Valid means a fair test, reliable means repeatable, accurate means close to the true value.
- Repeat trials and use the mean. Check outliers instead of ignoring them.
- Choose the right graph: line for continuous data, column for categories.
- First Nations knowledge is ICIP: use approved sources, name the community and ask permission.

## Quiz

Try these questions from the chapter quiz.

1. Shara tests how salt concentration affects seed germination. What is the independent variable?
   - A. Salt concentration
   - B. Number of seeds that germinate
   - C. Type of seed
   - D. Temperature of the room
   - Answer: A. Salt concentration. The independent variable is the one thing she changes on purpose.

2. In the same experiment, what is the dependent variable?
   - A. Salt concentration
   - B. Number of seeds that germinate
   - C. Volume of water
   - D. Size of the dish
   - Answer: B. Number of seeds that germinate. The dependent variable is what is measured as a result.

3. Why should each trial be repeated at least three times?
   - A. To make the test valid
   - B. To make the results more reliable
   - C. To change the independent variable
   - D. To remove all systematic errors
   - Answer: B. To make the results more reliable. Repeating and averaging lowers the effect of random errors, so results are more reliable.

The whole chapter quiz is on the page, for signed-in students: https://whizznotes.com/biology/working-scientifically/#quiz