P.03 Variables
Key Types of Variables
- Independent Variable:
- Definition: The variable you purposefully change to observe its effect.
- Example in Rennin Experiment: Concentration of rennin.
- Importance: Changing the independent variable allows you to examine its impact on the dependent variable.
- Dependent Variable:
- Definition: The variable you measure in response to changes in the independent variable.
- Example in Rennin Experiment: Rate of milk clotting (time taken for milk to coagulate).
- Importance: This variable’s response provides data to analyze the effect of the independent variable.
- Standardised (Controlled) Variables:
- Definition: Variables that are kept constant to ensure a fair test.
- Purpose: Ensures that changes in the dependent variable are solely due to the independent variable.
- Examples in Rennin Experiment:
- Temperature: Must be consistent to prevent it from influencing enzyme activity.
- Type of Milk: Different types may clot differently; using the same milk type ensures consistency.
- pH: Affects enzyme activity; must remain constant for accurate results.
Importance of Standardising Variables
- Maintaining Validity:
- Without controlling variables like temperature or pH, results may be inaccurate or inconclusive.
- Eliminating Confounding Factors:
- Ensures that only the independent variable (enzyme concentration) affects the outcome.
- Non-Essential Variables:
- Variables such as light level, time of day, and type of glassware are unlikely to affect enzyme activity in this context and do not need to be controlled.
Practical Approach for Experimental Design
- Identify the Variables:
- Decide on the independent variable (what you will change).
- Identify the dependent variable (what you will measure).
- List standardised variables that could impact results if not controlled.
- Plan for Control of Standardised Variables:
- Implement procedures to keep standardised variables constant throughout the experiment.
- Examples: Using a water bath to maintain temperature or using a pH buffer to stabilize pH.
- Conducting the Experiment:
- Change the independent variable systematically, measure the dependent variable for each change, and ensure that standardised variables remain constant.
Summary of Key Terms
| Term | Definition |
|---|---|
| Independent Variable | Variable deliberately changed in the experiment (e.g., rennin concentration). |
| Dependent Variable | Variable measured in response to the independent variable (e.g., milk clotting rate). |
| Standardised Variable | Variables kept constant to ensure results are due to the independent variable (e.g., temperature, pH). |
Understanding Range and Interval for Independent Variables
- Independent Variable: The factor that you purposefully change in an experiment to observe its effect on the dependent variable.
- Example: Rennin concentration in an enzyme activity experiment.
- Range:
- Definition: The spread between the lowest and highest values of the independent variable.
- Example: Using rennin concentrations from 0% to 1% in an experiment.
- Choosing Range: Often determined by available resources; e.g., if provided with a 1% solution, 1% would be your highest concentration, as you can only make dilutions from this stock solution.
- Interval:
- Definition: The spacing between the values within the chosen range.
- Example: Using intervals of 0.2% for rennin concentrations (0, 0.2, 0.4, 0.6, 0.8, and 1%) gives an interval of 0.2%.
- Alternative Interval Choice: Intervals based on a factor of ten (e.g., 1.0, 0.1, 0.01, 0.001) can be useful for observing effects over a wide concentration range.
Serial Dilution Method (for Creating a Range of Concentrations)
- Serial Dilution:
- A method for creating a range of progressively lower concentrations from a standard solution, useful for controlled experimentation with accurate intervals.
- Steps for Dilution:
- Start with a standard concentration (e.g., 1% solution).
- Transfer a specific volume of the standard solution into a new container.
- Add distilled water to dilute, achieving the desired concentration.
- Repeat for further dilutions as needed.
Example Serial Dilution Process
- Create 0.8% Solution:
- Transfer 8 cm³ of a 1% solution and add 2 cm³ of water to reach 10 cm³ of 0.8%.
- Create 0.6% Solution:
- Transfer 6 cm³ of the 1% solution, add 4 cm³ of water to make 10 cm³ of 0.6%.
- Further Dilutions:
- Continue the process, transferring progressively smaller volumes and adding water to reach desired concentrations.
Key Terms
| Term | Definition |
|---|---|
| Independent Variable | The factor changed in an experiment (e.g., rennin concentration). |
| Dependent Variable | The variable measured in response to changes in the independent variable. |
| Standardised Variables | Variables kept constant to ensure valid results (e.g., temperature, pH). |
| Range | Spread between the lowest and highest values of the independent variable (e.g., 0% to 1%). |
| Interval | Spacing between values within the range (e.g., increments of 0.2%). |
Summary of Steps for Changing Independent Variable in Experiments
- Choose the Range: Determine lowest and highest values based on available materials and desired outcomes.
- Set the Interval: Decide on a suitable spacing (e.g., equal increments or logarithmic scale).
- Prepare Solutions Using Serial Dilution: Create accurately spaced concentrations by diluting a standard solution as needed.
- Ensure Consistency: Use precise measurement tools and techniques to maintain accuracy across all concentrations.