7.2.2Additional lessons
Applying Technology to Process Data in Chemistry — IB Chemistry HL Revision Notes & Topical Questions
5 min read 6 parts Lesson 162 of 172
Part 1 of 6Spreadsheets for Calculations
Processing data by hand is slow and error-prone, so software is widely used.
Formulae
- A formula in a cell calculates results automatically and updates when the raw data is corrected, which saves time and avoids copying errors.
Statistics
- Built-in functions give the mean, standard deviation and range of a set of repeat readings in one step.
Unit columns
- Heading each column with its quantity and unit keeps calculations clear and prevents mixing cm³ with dm³.
Rounding
- Keep full values in calculations and round only the final answer to the correct number of significant figures.
Part 2 of 6Graphing Software
Graphing Software
Scatter plots
- These plot one measured variable against another and let a best-fit line or curve be added.
Trendlines
- Software fits linear, exponential or polynomial lines and reports the equation and R² value.
Linearising
- Plotting ln k against 1/T turns a curved relationship into a straight line whose gradient gives useful constants.
Error bars
- Error bars can be added from the uncertainty column, which shows how much a result may vary.
Part 3 of 6Databases and Modelling
1
Online databases give accepted values such as bond enthalpies, melting points and spectra for comparison with experiment.
2
Spectral databases let a measured IR or NMR spectrum be matched with a reference to help identify a compound.
3
Molecular modelling software builds three-dimensional structures and shows bond lengths, angles and shapes.
4
Simulations let variables such as temperature or concentration be changed quickly to test predictions safely.
5
Results from software must be compared with experiment because a model contains simplifying assumptions.
Part 4 of 6Using Software Well
Check the output
- Inspect the graph and values for obvious errors, such as a point far from the trend that may come from a typing mistake.
Cite sources
- Record the origin and date of any database value, so readers can trace the data.
Choose the fit
- A linear trendline should not be forced through data that is clearly curved, since this misrepresents the relationship.
Keep raw data
- Store the original readings unchanged in a separate sheet before any processing.
Part 5 of 6Worked Example
Question
- Five titres are 22.40, 22.50, 22.45, 22.55 and 22.60 cm³.
- Find the mean and the sample standard deviation.
- Sum = 112.50 cm³, so mean = 112.50 ÷ 5 = 22.50 cm³.
- Deviations from the mean are −0.10, 0.00, −0.05, +0.05 and +0.10 cm³.
- Sum of squared deviations = 0.0250; divide by n − 1 = 4 to give 0.00625; the square root is 0.079 cm³.
Answer Mean = 22.50 cm³, standard deviation = 0.079 cm³
Part 6 of 6Exam Checklist & Tips
7.2.2 – Key Points for the Exam
- Spreadsheet Software that stores data in cells and calculates results with formulae.
- Trendline A line or curve fitted to data points by software.
- Standard deviation A measure of how widely repeat readings are spread about their mean.
- Simulation A computer model used to predict how a system behaves when variables change.
- Linearising Changing variables so that a curved relationship plots as a straight line.
Common Mistakes
- Rounding values in the middle of a calculation, which builds up rounding error in the final answer.
- Trusting a high R² value as proof of a relationship when the data points are few or poorly chosen.
- Forgetting to label axes and units in graphs made by software, as defaults are often missing.
- Treating a database or simulation value as exact, without checking its source and conditions.
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