Presenting it
A clean spreadsheet, the variables you have chosen, and your statistical result if you ran one. If the numbers are still moving, stop here, remaking eleven figures because a depth reading changed is a bad evening.
- At least five different presentation techniques, each chosen for a reason
- Every figure numbered, titled, labelled and integrated into the text
- Any statistical result presented where it is used, not in an appendix
- A locational map that has become a data map
"Most appropriate technique" is a judgement you have to make, and be seen to make.
Six marks turn on whether the presentation is appropriate for the data type, whether a sufficient range has been used effectively, and whether conventions are followed. The default output of a spreadsheet is not a choice, and it reads like one that was never made.
Aim for at least five different techniques, each because it suits that variable. The number is our advice rather than an IB rule, but the principle is not: reports that stay in the middle band are usually the ones whose presentation is appropriate yet limited in variety, four bar graphs and a pie chart. The descriptor says "a sufficient range … used effectively", and five distinct, well-chosen techniques comfortably clears it.
These are sketches of the form, not finished figures. They show what each technique looks like and how its axes should be labelled; the shapes follow our own river, but there are deliberately no values on them. Your figures have to be built from your own spreadsheet, at full size, with a title, units and a key. Anything you could copy from this page would not be your work.
Any variable against distance from source, your workhorse. The line of best fit is what lets you describe a relationship rather than list nine separate points, and the r² beside it says how strong that relationship actually is. Both are one tick box in Excel or Sheets; step 6 explains how to read the r².
Site number on the x-axis instead of distance. This is the single commonest error in this IA, and it changes what the graph is even about.
Showing how the shape of the channel changes, not just its size. Two sites on one vertical and one horizontal scale, so the change is real rather than an artefact of the drawing.
Different scales between sites, which makes them incomparable. On its own autoscale, each of these two panels would look almost identical.
Altitude against distance; the spine of the whole investigation, and the figure a reader needs before any other.
Leaving it as a bare profile. It earns its keep twice over as the base for a second dataset plotted along the same axis.
Discharge or velocity, shown where they actually happened, the technique that most distinguishes a Geography IA from a set of graphs.
Symbols scaled by radius rather than area: set the radius from the square root of the value so the AREA carries the meaning, or the big ones are wildly exaggerated. And remember this is still a map; it needs all five BOLTS conventions and its basemap credited, exactly like the locational map in step 2, plus a key showing what the symbol sizes mean.
Genuinely categorical data, such as Powers roundness classes, frequency up the y-axis, the classes in their proper order along the x.
Using bars for continuous data, where a scattergraph shows the relationship better. Bars imply discrete categories; distance downstream is not one.
- Very angular (0)
- Angular (0)
- Sub-angular (2)
- Sub-rounded (15)
- Rounded (12)
- Well rounded (1)
What one sample is made of, as parts of a single whole. The roundness classes in one site's bedload are the one dataset in this investigation that genuinely fits, because every stone falls into exactly one class and the classes add to 100%.
Almost everything else. Discharge, velocity and width are not parts of a whole, so a pie of them means nothing. And your roundness hypothesis is about the change between sites; two pies side by side are far harder to compare than the paired bars above, which is why that comparison belongs in a bar chart and this does not.
Bed material, bank form, engineering, land use, and, as here, the precautions that keep your readings comparable between sites.
Annotations over ten words, which start counting against your limit. And annotations that name what is in the frame rather than saying something a reader could not see for themselves.
- May 2015: heavy rain, and discharge exceeds the channel
- Flooding on the Asse plain, at the railway and Paléo
- Flood-protection and renaturation scheme, from 2019
- About 4.5 km inside Nyon to be widened and reprofiled
- There, width and depth are a design decision, not distance downstream
- So a site there can sit off the trend, and you can explain why
A process or a chain of reasoning you would otherwise spend eighty words on. This one is the chain behind an anomaly on our own river, which is exactly the kind Criterion D (Written analysis) rewards.
Decoration. If a flow chart does not replace prose, it is not earning its space, and a chain of things a reader already believes replaces nothing.
Everything below is how we suggest you actually do it.
Integrated means next to the sentence it supports
The presentation and the written analysis must be integrated. No page of graphs, no gallery of figures at the end, no appendix full of the evidence for your argument.
In practice this means each figure sits beside the paragraph that discusses it, and that paragraph refers to it by number. If a reader has to flip pages to see what you are talking about, the two are not integrated however good each half is.
This has a consequence worth planning for: appendices are not read. Anything that matters has to be inside the report. Since tables of numerical data do not count towards your word limit wherever they sit, there is no reason to exile them, put them in the body, where they will be seen.
Plotting against site number rather than distance from source is the most common single mistake in this investigation, and it is quietly destructive.
Site numbers are equally spaced by definition. Your sites are not: on the Asse there is 2.3 km between the first two and just 40 m between sites 5 and 6. A site-number axis draws those two gaps identically, it stretches the top of the river and squashes the middle.
Worse, it changes what the graph is about. The question asks about distance from the source. A graph against site number cannot answer it, whatever the correlation says.
- Border
- Orientation
- Legend
- Title
- Scale bar
The five, in full, since the line above only names them. Every map in the report, locational or data, gets all five.
The two figures that are worth the most trouble
Channel cross-sections are the figure that shows most and is done worst. Plot depth against distance across the channel, with the water surface as a line at zero, so the shape of the bed is visible.
The rule that makes them work: the same scales at every site. Draw each cross-section with the same metres-per-centimetre on both axes and they become directly comparable; you can see the channel getting wider and deeper as a set. Let each one autoscale to fit its own box and you have drawn nine pictures of roughly the same shape, which is worse than useless because it hides the very change you are investigating.
The long profile is the other one. Altitude against distance from source is the spine of the whole investigation, and most reports draw it once and leave it. It is far more useful as a base: plot the profile, then place proportional symbols, bars or annotations for a second variable at each site along it. One figure then shows where the sites are, how steep the river is between them, and how the variable changes, a lot of information for one page.
Your sites fall from 711 m to 413 m over 8.9 km. Drawn to true scale that long profile is almost flat, 298 m of fall across 8,925 m of length.
So the vertical axis has to be exaggerated for the profile to show anything at all. That is normal practice and entirely acceptable. What is not acceptable is doing it silently.
State the vertical exaggeration on the figure itself, "vertical scale exaggerated ×20", and keep it identical on every profile you draw. An unlabelled exaggerated profile invites a reader to conclude the river is far steeper than it is.
Located data, on a map
This is the technique that most distinguishes a Geography IA from a set of graphs: your data has coordinates, so some of it belongs on a map rather than an axis. Proportional symbols, a circle at each site sized by discharge, or velocity, or bedload, put the pattern back in the place it came from.
Felt is the quickest route. Get your spreadsheet into shape with latitude and longitude columns in decimal degrees, share it with anyone-with-the-link, and load it into a new Felt map from that URL. Then size the symbols by the variable you want, adjust the colours and the legend, choose a basemap, and export the view as an image with the legend included.
Then apply the same judgement as any other figure. Proportional symbols show magnitude at located points, so they suit discharge or velocity. They are poor at showing a gradual trend along a line: for "does this rise steadily downstream?" a scattergraph is clearer. A report that uses both, each for what it is good at, is exactly what "most appropriate techniques" means.
If one site's discharge is four times another's and you make its circle four times the radius, it appears sixteen times the size. Proportional symbols are read by area, so area is what has to be proportional.
Most tools do this correctly by default. Check yours by comparing your largest and smallest symbols against the ratio of the actual values, and say in the caption that the symbols are scaled by area.
- Border
- Orientation
- Legend
- Title
- Scale bar
A data map is still a map. Same five conventions as the locational map in step 2, plus the basemap credited, and a key showing what the symbol sizes mean.
Before Felt can read your spreadsheet you have to share the Google Sheet with "Anyone with the link", then paste that link into Upload Anything → From URL. Leave it private and the import simply fails, with nothing on the map and no useful error.
Two other things Felt needs from the sheet: a latitude column and a longitude column, in decimal form, `46.409795`, not `46° 24' 35.26" N`. Right-click a point on map.geo.admin.ch and take the WGS 84 (lat/lon) pair.
Doing this by hand is equally acceptable, and the subject reports are consistently warm about hand-drawn work. Circles drawn to scale on a printed base map, with a legend showing what each size means, meets the same descriptor.
What the 400 words are actually for
Not describing your figures. "Figure 4 shows a scattergraph of velocity against distance from the source" tells a reader what they can already see, and every word of it comes out of the budget you need in step 6.
Spend them on the decisions instead. Why this technique for this variable. Why the scales are what they are. What you did about a site you left off a graph. Why Spearman's rather than something else, and what its result means for the hypothesis it was testing.
That is the difference between presentation that has been used and presentation that has been used effectively: the reader can see that each figure was chosen, not produced.
"Figure 6 is a bar chart showing the average bedload size at each of the nine sites, measured in centimetres, with site number along the bottom."
Thirty words that a glance at the figure would have supplied.
"Bedload was plotted as a scattergraph against distance rather than a bar chart by site, because the hypothesis concerns a continuous change with distance and bars imply discrete categories. Roundness, being an ordinal Powers class, is shown as stacked bars instead."
Forty words that show two decisions and the reasoning behind both.
If you ran a test, its result belongs in the analysis, at the point where you use it, not in an appendix, and not dropped in as a lone number at the end of a paragraph.
Report the coefficient, say whether it is significant, and say what that means for the null hypothesis you wrote in step 1. Three clauses, and it turns a calculation into evidence.
It can react to a figure you have already made. Describe your graph, say what you were trying to show, and ask whether it does; the same conversation you would have with a classmate.
It cannot choose your techniques or make your figures. Choosing the most appropriate technique for each variable is literally what Criterion C (Quality and treatment of information collected) awards; a generated chart is somebody else's decision about your data.
Ready for step 6?
0 of 12Print the figures out, or lay them side by side on screen, and read them as a stranger would. Anything you have to explain out loud is a figure that is not yet finished.
Step 6 is the written analysis: the largest criterion in the IA, the largest slice of the word count, and the one place where a shared investigation becomes unmistakably your own.
Anything marked “our river” is specific to the fieldwork we do together on the River Asse at Nyon: the sites, the equipment and the way we collect the data. Site coordinates and altitudes are from our own fieldwork records and the exact list can change from year to year, so check them against the sheet you are given on the day. Photographs are the author’s own, taken at the river.