A Level Physics A OCR

Planning

Planning

Identifying Variables

• Distinguish between independent, dependent, and control variables.
• The independent variable is the one you change in the experiment.
• The dependent variable is what you measure in the experiment.
• Control variables are all other factors which must be kept constant to ensure a fair test.

Formulating a Hypothesis

• A hypothesis is a scientific prediction about the expected outcome of an experiment.
• The hypothesis should be based on prior scientific knowledge.
• Include in it a scientific explanation that indicates an understanding of the physics relevant to the experiment.

Estimating Results

• An initial estimate of results can help identify potential problems in data collection before beginning the full experiment.
• This step also allows for an assessment of the range and spread of data which can guide decision making with regard to uncertainty analysis.

Safety Considerations

• Before starting an experiment, you should always consider any potential risks associated with the procedure.
• Ensure to reduce the risk of hazard in order to protect yourself and others.
• Organize your data collection strategy to reduce errors and ensure efficiency.

Practical Techniques

• Accurate data collection is essential. This often involves using suitable equipment and technical skills.
• Important techniques include correctly setting up equipment, taking accurate measurements, and repeating readings to estimate random uncertainties.
• You should consider any limitations or potential sources of error that may affect the quality of your data (e.g. parallax error).
• Keep good records of each step and the results, including diagrams of the setup and tables of observations.

Data Analysis

• Always review the data to identify any unexpected results or mistakes in data recording.
• Graphical methods can be utilised to present and interpret data.
• Calculate means and ranges of values, and consider sources of uncertainty and how they can affect the analysis.
• Conclusions should be clearly stated and justified with evidence from the data.

Evaluation of Method

• Critically evaluate your method to recognise areas that could be improved in the future.
• Identify systematic errors and explain how they could be minimised.
• Discuss how data treatments could be modified to reduce uncertainty.
• Reflect on the implications of the uncertainty upon the conclusions drawn.