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Tools and Inquiry — IB Physics skills

T.2.2 Applying Technology to Process Data in Physics — IB Physics HL Revision Notes & Topical Questions

5 min read 9 parts Lesson 5 of 22 1 quiz

📚 IB Physics HL Hub / Topical Revision
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Curriculum Equation Key قوانين الرقم الهيدروجيني والاتزان الأيوني - pH & Acid-Base Equilibrium FormulasFast Exam Solution
pH = -log[H⁺] | pOH = -log[OH⁻] | pH + pOH = 14 | [H⁺][OH⁻] = 10⁻¹⁴
Word Equation & Conditions: الرقم الهيدروجيني = -لوغاريتم تركيز أيون الهيدروجين | pH + pOH = 14
Location & Specifications: الاتزان الأيوني، كيمياء 3 ثانوي، التحصيلي، و AP Chemistry.
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Lesson summary

T.2.2 Applying Technology to Process Data in Physics — IB PHYSICS SL notes: Use spreadsheets, graphing software and computer modelling to process data, fit lines and check the output sensibly.As investigations get more complex, technology is essential to process, analyse and inte…

  • The software does not know whether the physics is sensible
  • Keep raw data separate from processed files
  • Data organisation
  • Data manipulation
  • Fill formulas down and check one row by hand
  • Use a scatter plot for continuous variables

Part 1 of 7Why process data with software

1
As investigations get more complex, technology is essential to process, analyse and interpret data efficiently.
2
It speeds calculations, reduces arithmetic errors and allows quick exploration of graphs.
3The software does not know whether the physics is sensible
  • The software does not know whether the physics is sensible set up the calculation correctly and check the results.
4Keep raw data separate from processed files
  • Keep raw data separate from processed files and record the operations done.

Part 2 of 7Spreadsheets

Spreadsheets (Excel, Google Sheets) organise, analyse and present data.
Data organisation
  • Data organisation enter raw data into rows and columns, categorised by parameter.
  • One column per variable with symbol and unit in the heading keeps repeated trials consistent.
Data manipulation
  • Data manipulation calculate averages, gradients, uncertainties and error propagation.
  • Statistical functions identify trends and reduce random uncertainty.
  • Built-in formulas automate repeated calculations, e.g. =AVERAGE(B2:D2).
Fill formulas down and check one row by hand
  • Fill formulas down and check one row by hand format to a sensible number of significant figures.

Part 3 of 7Graphical representation

Graphical representation
Graphs simplify complex data.
Line graphs and scatter plots show trends and correlations.
Bar graphs and pie charts help compare data.
Use a scatter plot for continuous variables
  • Use a scatter plot for continuous variables label axes with symbol and unit and add error bars.
Check the axis scales
  • Check the axis scales default axes may compress the data.

Part 4 of 7Fitting lines and curves

Fitting lines and curves
Add a trendline
  • Add a trendline display the equation and R2 for a linear fit.
LINEST (or SLOPE and INTERCEPT) returns the gradient and intercept with their uncertainties.
  • Compare with a hand estimate from best-fit and worst-fit lines; they should be the same order of magnitude.
R2 near 1 shows a close fit
  • R2 near 1 shows a close fit it does not prove that the model is correct.
Choose the curve type from the physics
  • Choose the curve type from the physics not the highest R2; a high-order polynomial fits anything.
Force a line through the origin only if the physics requires it
  • Force a line through the origin only if the physics requires it forcing it hides a systematic error.

Part 5 of 7Linearisation and checking outputs

Linearisation and checking outputs
Plot transformed variables to test models.
  • T2 against L for a pendulum.
  • ln A against t for decay.
  • 1/v against 1/u for lenses.
Compare the fitted gradient with the predicted value
  • Compare the fitted gradient with the predicted value and ask whether an intercept has physical meaning.
Check the output.
  • The gradient has units of y divided by units of x.
  • The size is plausible.
  • Two points on the line give the same gradient by hand.

Part 6 of 7Computer modelling

Computational models simulate real phenomena and give insight into complex processes.
Applications
  • Applications climate change, earthquake response of buildings and orbital mechanics.
  • Laboratory setups such as a damped spring-mass oscillator.
  • Virtual experiments covering a wider range of conditions quickly and safely.
Advantages
  • Advantages saves time and resources compared with purely experimental work.
  • Allows scenarios too dangerous, large or small for a laboratory.
  • Tests models and refines theoretical predictions.

Part 7 of 7More from the specification

More from the specification
Photocell timers and digital light gates
  • Photocell timers and digital light gates connecting electronic light gates to digital data loggers allows precise millisecond velocity measurement.
Sensor
  • Device converting a physical quantity into an electrical signal.
Simulation
  • Computer model imitating a physical system.
Temperature
  • Measure of the average kinetic energy of the particles.
Database
  • Structured collection of data that can be searched and analysed.
Light gate
  • A sensor that starts or stops a timer when a beam is interrupted.
Projectile motion
  • Two-dimensional motion with constant horizontal velocity and vertical acceleration g.

Key terms

TermMeaning
SpreadsheetSoftware arranging data in rows and columns and calculating with formulas.
TrendlineBest-fit line or curve added to a graph by software.
R2Number from 0 to 1 showing how closely a fit follows the data.
LINESTSpreadsheet function returning gradient, intercept and their uncertainties.
ResidualDifference between a data point and the fitted value.
Computer modelProgram simulating a physical system using rules and assumptions.

Avoid these mistakes

1
Trusting R2 alone as proof that a model is correct.
2
Using a line chart instead of a scatter plot — it distorts uneven x-values.
3
Keeping the software's default decimal places — this gives false precision.
4
Forcing a trendline through the origin when the data do not support it.
5
Not checking the units or order of magnitude of values from the software.

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