Data analysis

⚙️ CRITERION B: DATA ANALYSIS (6 marks total)

This section focuses on how well you record, process, and analyze the data you’ve collected, especially in terms of clarity, uncertainty treatment, and accuracy.

✅ 1. Clarity and Precision in Communication

Your data tables, graphs, and calculations must be:

• Clearly presented

• Neatly organized

• Labeled properly

• Easy to follow

✔️ What to Do:

• Use consistent units and significant figures.

• Label all tables (e.g. “Table 1: Time for 10 pendulum oscillations at various lengths”) and all graphs (with axes labeled and units).

• Include headings, titles, and legends where needed.

• Make sure everything is logically arranged.

🧠 Example:

Graph: Period vs. √Length, with error bars and a best-fit line.

✅ 2. Consideration of Uncertainties

This is where you show your understanding of experimental uncertainty—an essential part of physics.

✔️ What to Do:

• Include uncertainties in all measurements (e.g., ±0.01 m).

• Use proper error propagation in calculated values (add, subtract, multiply, divide).

• Show how you calculated uncertainties (e.g. range/2 for repeated trials or based on instrument precision).

• Include error bars on graphs if applicable.

🧠 Example:

Uncertainty in length: Meter ruler precision is ±0.001 m
Uncertainty in time: Based on stopwatch reaction time (±0.2 s), average over 10 oscillations to reduce error
Propagation: T=t/10, so ΔT=Δt/10 ​

On Graph: Use vertical error bars to reflect uncertainty in period.

✅ 3. Accuracy in Data Processing

Your calculations must be:

• Mathematically correct

• Relevant to your research question

• Reflect a good understanding of the physics involved

✔️ What to Do:

• Show sample calculations clearly with all steps, units, and significant figures.

• Use appropriate mathematical models, such as linear regression, logarithmic fits, or theoretical formulas.

• Use software or tools for precision (Excel, LoggerPro, Desmos, GeoGebra, etc.), but explain what you did.

• If you’re comparing theoretical vs. experimental values, calculate percentage error.

🧠 Example:

Sample Calculation:

✅ 4. Types of Data

You should present:

• At minimum, quantitative data (numbers you measured or calculated)

• You may also include qualitative data (observations, patterns, visual cues), but it must support the quantitative analysis

✔️ What to Do:

• Collect measurable quantities (mass, time, force, voltage, etc.)

• Add brief observations if helpful (e.g., “At larger angles, the pendulum’s motion became less regular.”)

• Make sure your data is relevant to your RQ

🧠 Example:

• Quantitative: “Measured voltage across the resistor at 5 different current values.”

• Qualitative: “The resistor warmed slightly at higher currents, which may affect resistance.”

✅ Summary Checklist for Criterion B