Introduction to Experimental Design

Welcome to the "engine room" of Human Biology! Before scientists can discover new medicines or understand how our bodies work, they must design experiments that are fair, accurate, and reliable. In your Pearson Edexcel IGCSE exam, you will often be asked to design an investigation or evaluate someone else’s method. This chapter will give you the tools to think like a scientist and pick up those essential practical skills marks.

Note: This chapter focuses on the logic of experiments. For specific details on how to test for glucose or measure breathing rates, see the "Practical investigations" chapters.

Section 1: The Three Types of Variables

A variable is anything that can change, be measured, or be kept the same in an experiment. Understanding these is the first step to a perfect practical plan.

1. The Independent Variable

This is the factor that you choose to change. It is the "cause" in the experiment. For example, if you are investigating how temperature affects enzyme activity, the temperature is your independent variable because you are choosing which temperatures to test (e.g., \( 20 ^\circ\text{C} \), \( 30 ^\circ\text{C} \), \( 40 ^\circ\text{C} \)).

2. The Dependent Variable

This is what you measure as a result. It is the "effect." In our enzyme example, the dependent variable might be the volume of oxygen gas produced in \( 1 \) minute, measured in \( \text{cm}^3 \).

3. Control Variables

These are all the other factors that you must keep the same. If you don't control these, you won't know if your results were caused by your independent variable or by something else! This is called making the test valid.

Common Control Variables in Human Biology:

  • Volume of a solution (e.g., \( 10 \text{ cm}^3 \) of starch solution).
  • Concentration of a chemical (e.g., \( 1\% \) amylase).
  • Temperature (if it is not the independent variable).
  • pH (often kept constant using a buffer solution).
  • Time (e.g., allowing a reaction to run for exactly \( 5 \) minutes).

Quick Tip: If an exam question asks for a control variable, never just write "amount." Use specific words like volume, mass, or concentration.

Section 2: Designing a Perfect Investigation (The CORMS Mnemonic)

When you are asked to "Describe an investigation," use the CORMS reminder to make sure you cover every point needed for full marks:

C – Change: What is your independent variable? State the range of values you will use (e.g., "Change the pH from \( \text{pH 2} \) to \( \text{pH 10} \)").
O – Organism: What biological material are you using? Keep it the same (e.g., "Use seeds from the same species" or "Use humans of the same age and fitness level").
R – Repeat: To make results reliable, you must repeat the experiment at least \( 3 \) times at each level and calculate an average (mean). This also helps you spot anomalies (results that don't fit the pattern).
M – Measure: What is your dependent variable? Mention the equipment you will use and the time frame (e.g., "Measure the volume of gas using a gas syringe every \( 30 \) seconds").
S – Same: List at least two control variables you will keep the same to ensure a fair test.

Section 3: Evaluating the Method

Once an experiment is finished, we have to look back and ask: "How good was it?" In Human Biology, we use three specific words to evaluate work. Don't worry if these seem similar; here is how to tell them apart:

1. Reliability

Can you trust the result? An experiment is reliable if you get the same result every time you repeat it. You improve reliability by repeating the experiment and identifying anomalous results (outliers).

2. Accuracy

How close is your measurement to the "true" value? You improve accuracy by using better equipment. For example, using a gas syringe to measure volume is more accurate than counting bubbles, because bubbles can be different sizes!

3. Validity

Is the experiment a "fair test"? An experiment is valid if you have successfully controlled all variables so that only the independent variable affects the dependent variable. If you forgot to control the temperature, your experiment is no longer valid.

Quick Review:
- Reliability = Repetition.
- Accuracy = Correctness/Equipment.
- Validity = Fairness/Control.

Section 4: Safety and Precision

When describing a safe technique, you should identify a specific hazard and how to manage it:

  • Hazard: Hot water baths. Safety: Use tongs or heat-proof gloves.
  • Hazard: Corrosive chemicals (like acids). Safety: Wear safety goggles and a lab coat.
  • Hazard: Scalpels/Sharp tools. Safety: Always cut away from the body on a hard surface.

Recording Measurements with Precision:
Always record measurements to an appropriate number of decimal places or significant figures. For example, if your weighing scale shows \( 1.25 \text{ g} \), don't round it to \( 1 \text{ g} \), as you lose the precision of the instrument.

Section 5: Drawing Conclusions

A conclusion is a statement that explains what the data shows. To draw a valid conclusion:

  1. State the trend: "As the temperature increases, the rate of reaction also increases."
  2. Use data from the results to support your point: "The rate was highest at \( 40 ^\circ\text{C} \) (\( 10 \text{ cm}^3/\text{min} \)) and decreased to \( 2 \text{ cm}^3/\text{min} \) at \( 60 ^\circ\text{C} \)."
  3. Give a biological reason: "This is because the enzymes were denatured at high temperatures."

Common Mistake to Avoid:
Don't confuse correlation with causation. Just because two things happen at the same time (correlation) doesn't always mean one caused the other! Scientists must evaluate if there is a biological link.

Key Takeaway Summary

- Independent variable: What you change (C in CORMS).
- Dependent variable: What you measure (M in CORMS).
- Control variables: What you keep the same (S in CORMS).
- Repeats: Essential for reliability and finding averages.
- Validity: Ensuring only the independent variable causes the change.
- Safety: Always match the precaution to the specific hazard.

For more information on the math side of things (like calculating a mean or drawing a graph), check out the chapter on "Data handling, graphs and calculations".