2
Graphing
2.1 Introduction
Most people respond better to pictures than words and numbers, so even a table of frequencies is still
not the best way to present data. Graphs show trends and differences in data very quickly, and
different types of graphs are available to show the data in various ways.
GENERAL PRINCIPLES FOR CONSTRUCTING GRAPHS
You should apply the following general rules when constructing a graph:
• axes labelled clearly
• informative title
• axis scale is the same all the way along – if 0-10 covers 1 cm, then so should 90-100 etc
• the axis scales must be shown
• where multiple series are plotted on the same graph, make it clear which data belongs to which
line/column by the use of legends
• don’t over-complicate the graph by the use of too many colours/gridlines/3-D (see below)
• the measured variable should be plotted on the vertical axis
FORMATTING ISSUES – Excel charting in general
Excel’s graphing function has so many options, it becomes a mixed blessing. Some of the appearance
options tend to swamp the graph with unnecessary “bells and whistles. Do not accept the default
settings without thinking “can I make this look better?”
2D vs 3D columns etc
There is no doubt that “3-dimensional” columns look better than plain rectangles. However, they can
make it difficult to judge where the top of the “column” is, relative to the vertical axis. Gridlines (see
below) can help in this regard. However, 3D pie charts are too be avoided like the plague. This will be
explained further later in this chapter.
Gridlines
As noted above, they help with 3D columns, but are less needed with 2D columns, and are totally
distracting with line-based graphs.
Legend
A legend is crucial where there are more than one data series, but totally useless when there is only
one (e.g. calibration graph). When the legend is necessary, it is made useless if the labels are simply
the default Series 1, Series 2 etc. Make sure you fix this using the Series/Name (how to do this it will
depend on which version of Excel you have).
Background
Older versions of Excel used to default to a graph background of mid-grey. On the printed page, this
becomes very distracting, and should be changed to no background (or white if you are copying it to a
Powerpoint). Fortunately, this doesn’t happen in newer ones.
Colours & patterns
If you have to change colours of lines, column, points etc, make sure they don’t end up similar
brightness, because black & white printing will mask the difference. Avoid patterns – they are too hard
on the eyes.
Sci. Info Skills
TYPES OF GRAPHS
Excel allows you access to numerous graph (chart) types, but be warned that not every type is useable
for every type of data set. Table 2.1 provides some guidance as to what each can be used for (in the
context of this subject, but the best advice is to ask yourself the following question when you have
created a graph:
Does this graph actually tell me what I want it to?
If the answer is anything but a resounding yes, it is back to the drawing board!
TABLE 2.1 Excel chart types
Excel chart type
Used for
Column, bar, cylinder,
cone, pyramid
Plotting frequencies for category data; the only difference between them
is appearance – a matter of personal preference
Line
Only useful for plotting frequencies for tallied numerical data where a XY
scatter doesn’t work (eg group values on horizontal axis); must not be
used for category data
Pie, doughnut
To show relative proportions of different categories; doughnut allows
multiple different sets to be compared
XY scatter
numerical data where two variables have some relationship to each
other, eg concentration vs time, temperature vs CO2, absorbance vs
concentration
Area
A line graph where the space underneath is filled with a solid colour; can
be used for multiple related sets (eg classes of wastes)
Radar
Allows more than 2 variables to be plotted for different data sets; not
widely used
Bubble
Allows a 3rd variable to be plotted on a XY chart using the diameter of the
bubble
Stock
Designed specifically for stock market graphs
Line-Column
A mixed format graph as the name indicates
COLUMN TYPE GRAPHS
This includes bar, cylinder, cone and pyramid charts offered by Excel. Column type graphs plot
frequency (or relative frequency) on the vertical (with the exception of bar graphs, where it is the
horizontal) axis, and the category value on the horizontal axis (see Figure 2.1).
Sci. Info Skills
Population Density
35
No. of countries
30
25
20
15
10
5
0
50
100
150
200
250
300
350
400
Popn/sq. km
FIGURE 2.1 (a) Column chart
Population Density
400
350
Popn/sq. km
300
250
200
150
100
50
0
5
10
15
20
25
30
35
No. countries
FIGURE 2.1(b) Bar chart (same data used)
CLASS EXERCISE 2.1
Does either of the above graphs illustrate the data better?
Where you have multiple data sets with the same categories (such as Table 2.3), they work better
when plotted together rather than separately, just as the combined table does. There are two ways
of approaching this, depending on the data:
•
multiple column/bars per category (Figure 2.2a)
•
stacked columns (2.2b) - only appropriate where the data makes sense when it is added together
Sci. Info Skills
(a)
70
60
50
Urban
Undeveloped
40
30
20
10
0
Native
Introduced
Not identified
100
(b)
90
80
70
60
Not identified
Introduced
50
Native
40
30
20
10
0
Urban
Undeveloped
FIGURE 2.2 Multiple set column graphs (a) side-by-side and (b) stacked
CLASS EXERCISE 2.2
Which graph in Figure 2.2 is better at portraying the data?
Sci. Info Skills
Figure 2.3 shows a different way of multiple-column plotting the same data as above. It is not better
or worse, simply different. You need to consider what you are trying to illustrate.
70
60
50
40
Native
Introduced
30
Not identified
20
10
0
Urban
Undeveloped
FIGURE 2.3 Alternative to 2.2(a)
120
100
Undeveloped
80
Urban
60
40
20
0
Native
FIGURE 2.4 Inappropriate alternative to 2.2(b)
CLASS EXERCISE 2.3
What is wrong with Figure 2.4?
Introduced
Not identified
Sci. Info Skills
FORMATTING ISSUES – Column graphs
Since there are at least 5 different styles (column, bar, cone etc), think about this first
Then consider whether a 3D graph will be more distracting than useful.
LINE GRAPHS
It is easy to mistake line and scatter charts in Excel, and imagine they are the same thing. In reality,
line charts are basically for the same type of data as column type graphs, except they must not be used
for category data, only tallied numerical data, as shown in Figure 2.5 (which uses the same data as the
column & bar graphs above).
Population Density
35
30
25
20
No. countries
15
10
5
0
<50
50-100 100-150 150-200 200-250 250-300 300-350
>400
Popn/sq. km
FIGURE 2.5 Line graph showing frequencies of tallied groups (using the same data as in Figure 2.1)
CLASS EXERCISE 2.4
How does the line graph compare to the column/bar graphs for this data?
CLASS EXERCISE 2.5
Why is a line graph wrong for plotting category data?
Sci. Info Skills
FORMATTING ISSUES – Line graphs
The only point of using a line graph is to put a line in, so don’t leave it as dots. Since it has to
be (no choice in this) a “join-the-dots” line, it isn’t necessary to plot both the line and the data
points.
Make sure the line is thicker than default.
But probably the best advice is to think first: should I use a category or scatter graph instead?
SCATTER GRAPHS
When you want to draw a graph with a line in it, this should your first port of call. To make a sensible
line-based graph, both axes need a number associated with them. In other words, two measurements
should have been made about that particular item, eg absorbance and concentration, pH and time. If
there is only one measurement, it is not possible.
The scatter graph shows the correlation between the two variables, ie whether one changes in
a consistent way when the other changes. This doesn’t have to be a perfect straight line, like in
calibration graphs.
Excel offers the option of plotting the graph with or without the line, and with or without the
points. You might think the line should always be shown, but that is not the case. Sometimes, simply
the points are sufficient.
If there is an obvious connection between the points, eg the measurements have been made at
different times or at different distances, but on the same basic population, then a line is a reasonable
way of showing that they are connected (see Figure 2.6).
If the two measures have been made on totally different but related items, then a line is not
appropriate, and it is best to simply show the points (see Figure 2.7).
If you do include the line, the decision needs to be made about whether to show the points. If
the line is a join-the-dots, it is not so important to show the points (Figure 2.6), but if it is a best-fit
line, it is essential, otherwise it might give the impression that the points are perfectly in line (Figure
2.8).
340
Concentration (ppm)
335
330
325
320
315
310
305
300
1958
1960
1962
1964
1966
1968
1970
1972
FIGURE 2.6 Scatter graph showing line showing time connection of measurements
1974
Sci. Info Skills
2.3
2.1
Nitrate (mg/L)
1.9
1.7
1.5
1.3
1.1
0.9
0.7
0.5
6
6.5
7
7.5
8
8.5
9
pH
FIGURE 2.7 Scatter graph with points only
1
Abs.
0.75
0.5
0.25
0
0
5
10
15
20
Conc. (mg/L)
FIGURE 2.8 Scatter graph showing dots and best-fit line
FORMATTING ISSUES – Scatter graphs
Make sure the line is thick enough to be clearly visible.
If you have more than one line on the graph, make sure that they differ in style (solid, dotted,
dashed), and are not light colours, to ensure it is readable when printed.
When using join-the-dots, avoid the auto-smoothed line that Excel defaults to.
Sci. Info Skills
PIE AND DOUGHNUT GRAPHS
Pie charts can also be used for category data, where the categories are represented by segments of a
circle. The size of the segments is proportional to relative frequency (or proportion) of each category
(see Figure 2.9). A pie chart, therefore, displays information in a similar way to each of the stacked
columns in Figure 2.2(b).
Only data collected from the same population should be grouped into a pie chart, for example
weights of the different types of recycled materials collected. If related measurements come from
different populations – for example masses of paper in recycling from different suburbs – then a pie
chart is incorrect.
Not identified
Introduced
Native
FIGURE 2.9 Typical pie chart
Likewise, it would be inappropriate to leave some categories from a measurement out entirely,
as that would artificially increase the importance of the others.
Doughnut graphs allow two related data sets to be plotted together, but can be confusing to
read, and are not recommended. Stick to stacked column graphs.
FORMATTING ISSUES – Pie charts
Firstly, do not use 3D pie charts under any circumstances (explained later).
If you intend to print it out in monochrome, be careful to avoid adjoining segments of the
same colour intensity (two dark segments next to each will merge).
Placing the labels next to the segments, rather than in a box-type legend will help make
identification easier. It is not necessary to include values and especially percentages in the
label.
If you want to emphasise a particular category, it is common practice to make that segment
slightly displaced from the main pie (like a serve of pie that has been lifted out slightly) (as
shown).
Sci. Info Skills
Assignment 2
Go to the website and download the two files - data and questions.
2.2 Bad graphs
The basic intention of a graph is to pictorially display data in a sensible and meaningful way. However,
it is true to say that there are many graphs in the public domain that are constructed so that they fail
to show the true meaning of the data. There are two basic reasons why this happens:
•
poor design
•
intentional deception
POORLY DESIGNED
Apart from the various aspects described in the previous section, poor graph design can come about
through:
•
plotting the wrong data
•
carelessness
•
over-complication
•
duplication of information
EXAMPLE 2.1
Fortune magazine is one of the biggest magazines for
those people in big business. This proves that a lot of
money doesn’t automatically make for a good graph.
Before your teacher gives you the answers, think about
the following:
(i) what information is the graph trying to provide?
(ii) what problem(s) do you see with the graph?
(iii) how would you fix the problem(s)?
Sci. Info Skills
EXERCISE 2.6
For the following graphs, all of which have been published:
(i)
what information is the graph(s) trying to provide?
(ii)
what problem(s) do you see with the following graphs?
(iii)
how would you fix the problem(s)?
(a)
(b)
Note that the original was in monochrome.
This one can’t be printed because of the colours. Assume you could actually read the text.
Source: http://lilt.ilstu.edu/gmklass/pos138/datadisplay/chart_clutter_examples.htm
Sci. Info Skills
EXERCISE 2.6 (CONT’D)
(c)
(d)
Sci. Info Skills
EXERCISE 2.6 (CONT’D)
(e)
Sci. Info Skills
EXERCISE 2.6 (CONT’D)
(f)
If you haven’t printed this out in colour, the lighter un-dotted line is distinguished by colour and
relates to the left hand vertical axis.
Sci. Info Skills
EXERCISE 2.6 (CONT’D)
(g)
Sci. Info Skills
EXERCISE 2.6 (CONT’D)
(h) Another that may not print very well, relying on colour darkness variations.
Sci. Info Skills
DELIBERATELY DECEIVING
An English prime minister of the late nineteenth century said that there were three kinds of lies: lies,
damned lies and statistics. Graphs are powerful story-tellers, particularly for people in a hurry. It is
quite possible for the truth to be hidden in the detail of a graph, and for the picture to distort this
truth. There are various ways that this can be done:
•
hiding elements of the graph
•
distorting elements of the graph
•
overemphasising one element of the graph
•
making unfair comparisons
If we were doing magic tricks on stage, this would be called “sleight of hand”, or in politics, just
everyday business. Remember the key aspects of a graph is the picture, and that is what the graph liar
relies on.
Hiding elements
If a key piece of information necessary for the viewer to understand what the data is saying is taken
away, then all that is left is to look at the picture and get the story from it.
The most commonly missing graph element that is removed is the title, but this is less serious
than you might imagine. Why? The axes labels or the text surrounding the graph might tell you enough
information anyway.
Far more serious is the removal of the scale from one or both axes.
EXAMPLE 2.2
The graph below shows the trend in carbon dioxide levels above Hawaii from 1958 to 1974. It will be
referred to a number of times.
400
ppm CO2
370
340
310
280
1950
1960
1970
1980
1990
2000
2010
Sci. Info Skills
EXAMPLE 2.2 (CONT’D)
(a) Is it a problem that the graph has no title?
Yes, while we can tell what is being graphed, we don’t know where the measurement have been
taken from (global average?).
How about the same data, plotted without a vertical scale?
ppm CO2
(b)
1950
1960
1970
1980
1990
2000
2010
Yes, the picture is the same, but without anything to compare to, the graph is really meaningless.
Different people looking at this would interpret it quite differently. Some would be concerned, others
not. A graph should tell the same story to everyone.
THE LESSON TO BE LEARNED
If there is no title and nothing else tells you what it is about, ignore the graph entirely!
If there is no axis scale, again ignore it!
Distorting elements
Distorting one of the elements of the graph leads to a false picture because something has become
exaggerated. The most commonly exaggerated element is the axis scale, even when it is shown.
Remember people look at the picture. Also is this category are the fancy graphical images where a
picture of the actual item being measured is used in the graph.
Sci. Info Skills
EXAMPLE 2.3
Let’s fiddle with the vertical scale, but show it this time, just not very distinctly.
(a) Now the same data plotted by someone who wants to reduce the apparent rise in CO2 levels.
600
ppm CO2
4 50
300
150
0
1950
1960
1970
1980
1990
2000
2010
Just looking at the picture (with no scale to refer to) makes it seem that CO2 levels aren’t rising very
fast at all.
(b)
Now the same data plotted by someone who wants to make the rise in CO2 levels look very
serious.
390
ppm CO2
3 70
3 50
330
3 10
1950
Now we’re worried!
1960
1970
1980
1990
2000
2010
Sci. Info Skills
With line-based graphs, there are no right or wrong ranges for axes scales as long as the scale is shown.
You don’t have to start at 0, but the two examples above are extreme cases and clearly intended to
deceive. The first one, with some white space above and below, seems a reasonable compromise.
There mightn’t be a rule for axis scales for line/scatter graphs, but there definitely is one for
column type graphs: you must start the vertical axis at 0 since the size of the column is proportional to
the value. Twice the value means the column must be twice as long. Not helping here is Excel’s default
to the wrong scale.
EXERCISE 2.7
The graph below shows the energy consumption in the USA at 5 yearly intervals from 1980. This is
properly constructed.
100
trillion Btu
75
50
25
0
1980
1985
1990
1995
2000
2005
Here is the same data, plotted by someone with an interest in distorting the data. What are they
trying to imply to the viewer of the graph? How have they done it?
100
trillion Btu
95
90
85
80
75
1980
1985
1990
1995
2000
2005
Sci. Info Skills
The author of these notes has actually heard a professional speaker actually say that some measure
had doubled from the previous year on the basis of a column chart, but a close examination of the
vertical axis scale showed that it started at 40, and therefore caused the exaggeration because the
previous year had a value of 42 and the current year 44!
There is one very bad distortion of the axis scale that was in the list of no-no’s at the start of this
section: inconsistent scaling. The scale should be consistent all the way along. For example, if 1 cm =
1 year at the left hand end, it should also be the same at the right hand end. Just because it is general
graph no-no doesn’t stop people using it to deceive.
EXAMPLE 2.4
Let’s go back to the “good” vertical scale (and make sure people can actually see it), but monkey
around with the horizontal. What does this graph suggest?
400
ppm CO2
370
340
310
280
1958
1968
1978
1994
It looks like there has been a rapid rise in CO2 from the late 80s, but what really has happened is that
the scale on the right hand end is compressed.
And yes, this has been done with Excel! Anyone like to suggest how?
One very popular trend of recent – not available to you on Excel – is the use of relevant pictures
instead of bars or columns. Instead of a plain old coloured rectangle showing the increase in oil
production, you use a picture of an oil drilling rig and make it larger as the value of oil production
increases. But there is a problem.
Sci. Info Skills
EXAMPLE 2.5
In principle, this is an visually interesting way of presenting the growth in oil production over time.
But there is something wrong with it – what?
5.8
billion
2.9
billion
1.4
billion
1975
1960
1990
This may not look as good but it is not misleading. It is better than stretching the graphic in one
direction only.
1960
1975
1990
THE LESSON TO BE LEARNED
Always look at the axis scales before making a judgement!
Look carefully at fancy graphic column charts.
Sci. Info Skills
Over-emphasising one component
If you want to “sell” one particular item in a graph, make it stand out more than it should. 3D pie
charts are notorious for this – even if you want to be objective and even-handed you can’t – which is
why you should never use them. 3D pie charts always over-emphasise the importance of the front
sector because you mentally perceive the front of the pie to be part of the sector and therefore make
it seem larger.
EXAMPLE 2.6
Here gas looks more important than coal.
Coal
Oil
Renewables
Nuclear
Gas
Here it is the other way round.
Nuclear
Gas
Oil
Renewables
Coal
They are actually of equal value.
Sci. Info Skills
Line graphs where one line is much darker (more prominent) than others emphasises it, which can be
used for good reasons, but also could be misused.
EXERCISE 2.8
What do you think is going on here?
9
8
7
mg/L effluent
6
Zn
5
4
3
2
Pb
1
0
2001
2002
2003
2004
2005
2006
2007
THE LESSON TO BE LEARNED
Look past the overly obvious and don’t miss the detail.
Ignore 3D pie charts – try to find the data it came from.
Unfair comparisons
Any time you see two separate graphs compared side by side, be wary. Differences in numerical value
will be masked because the graph will have scaled (in terms of physical size) the value differences out.
This is mainly a problem with column and pie charts. When two items being compared are in the same
graph, then they will be scaled according to their relative amounts. However, when they are in
separate graphs, then unless the scaling is exactly the same, differences will disappear.
Sci. Info Skills
EXERCISE 2.9
What are the following graphs trying to tell you about energy output in the US?
7
25
6
20
Renewables
5
Coal
15
4
3
10
2
5
1
0
0
1960
1970
1980
1990
2000
1960
1970
1980
1990
2000
How should they have been plotted?
EXERCISE 2.10
Now for some real graphs. For each:
1.
describe what the PICTURE ONLY indicates
2.
explain where the lying is going on
3.
describe how the graph should have been done to be accurate
Source: http://junkcharts.typepad.com/junk_charts/
(a)
Here is Steve Jobs, the founder of Apple Corporation, marketing a new product (not possible to
print this one).
Sci. Info Skills
EXERCISE 2.10 (CONT’D)
(b) Some more computer-related deception.
(c)
Surely someone’s having a joke here?
Sci. Info Skills
EXERCISE 2.10 (CONT’D)
(d) Crime figures from the US. The three columns per city are for the 3 different years.
(e)
A report on steroid use in American baseballers. Bear in mind that most teams have 3-4 times
as many pitchers as any other position player.
Sci. Info Skills
EXERCISE 2.10 (CONT’D)
(f)
The effect of inflation – top graphic represents 1958, then each 5 years.
(g)
ODA is an acronym for Overseas Development Assistance.
Sci. Info Skills
Interpreting graphs
There is a skill in creating a “good” graph which tells the story that you want it to, objectively and
clearly. Likewise, gaining information from other people’s graph is equally important.
EXERCISE 2.11
The graphs for these exercises are on separate pages following.
(a) Monthly rainfall data - Newcastle
1.
What type of graph is this?
2.
What information is the graph providing?
3.
Can you see any problems with the graph?
4.
Which month has the highest average rainfall?
5.
What is the rainfall for that month?
6.
Which month has the lowest average rainfall?
7.
What is the rainfall for that month?
8.
Which month has the highest average number of raindays?
9.
What is the number of days for that month?
10.
Which month has the lowest average number of raindays?
11.
What is the number of days for that month?
Sci. Info Skills
EXERCISE 2.11 (CONT’D)
(b) Trend in number of hot days.
1.
Give an example of a region showing an increase of 5 hot days/10 years.
2.
Give an example of a region showing an increase of 2 hot days/10 years.
3.
Give an example of a region showing a decrease in hot days.
4.
Give FIVE important pieces of general information to be gained from this graph.
(c)
1.
Average annual thunder days
Where in Australia has the greatest amount of thunder?
2.
Where in Australia has the least amount of thunder?
3.
Is there a general trend in thunder behaviour from north to south? What is it?
4.
Give TWO examples of regions that are exceptions to the basic trend?
(d)
1.
Air temperature vs wind speed
What type of graph is this?
2.
Which axis belongs to windspeed? Air temperature?
3.
What is the (i) lowest and (ii) highest windspeed recorded?
4.
What is the (i) lowest and (ii) highest temperature recorded?
5.
What conclusions can you draw from the graph?
Sci. Info Skills
EXERCISE 2.11 - GRAPHS
(a)
Sci. Info Skills
EXERCISE 2.11 - GRAPHS
(b)
Sci. Info Skills
EXERCISE 2.11 - GRAPHS
(c)
Sci. Info Skills
EXERCISE 2.11 - GRAPHS
(d)
Air Temperature (deg C) vs Windspeed (knots)
Data measured every 10 minutes over the last 5 days – Casey station, Antarctic
Sci. Info Skills
EXERCISE 2.12
Below is a “map” showing ozone concentrations in the atmosphere above an Antarctic monitoring
station in 2006. The colours are important. Use it to answer the questions on the next page.
Sci. Info Skills
EXERCISE 2.12 (CONT’D)
(a) Given the ozone layer is a zone of the atmosphere with relatively high concentrations of ozone,
what is its altitude range?
(b)
Given the ozone hole is a loss in concentration in the layer, in which months does it occur?
(c)
You are required to draw a graph showing the change in ozone concentration in the ozone
layer across the year. How could you do it?
(d)
You are required to draw a graph showing the change in ozone concentration in the
atmosphere at two times during the year to demonstrate the difference between “normal” and
the ozone hole period. How could you do it?
(e)
You are required to answer the question “Has the ozone hole decreased?”. How could you use
information from this 2006 map to help answer this question?
(f)
What other information would you need?
Sci. Info Skills
EXERCISE 2.13
You are provided with graphs and tables summarising a year’s worth of pollution data for Sydney
measured in three sub-regions: Central East, North West and South West.
You are required to use these summaries to answer the following questions.
1. How does air pollution in Sydney vary throughout the year?
2. How does air pollution in Sydney vary geographically?
Look at each and find evidence relating to the two questions above (note that you may not find
evidence for both questions from an individual summary).
Summary 1
Does this summary provide evidence to help answer with Q1? If so, what is it?
Does this summary provide evidence to help answer with Q2? If so, what is it?
Sci. Info Skills
Summary 2
Does this summary provide evidence to help answer with Q1? If so, what is it?
Does this summary provide evidence to help answer with Q2? If so, what is it?
Sci. Info Skills
Summary 3
Does this summary provide evidence to help answer with Q1? If so, what is it?
Does this summary provide evidence to help answer with Q2? If so, what is it?
Sci. Info Skills
Summary 4
Does this summary provide evidence to help answer with Q1? If so, what is it?
Does this summary provide evidence to help answer with Q2? If so, what is it?
Sci. Info Skills
Summary 5 - Low/Medium/High Readings Monthly By Region
Low, medium and high are gradings (categories) given based on the actual numerical pollution values.
Central East
J
F
M
A
M
J
J
A
S
O
N
D
L
26
22
25
25
28
26
26
29
27
22
21
24
M
4
5
5
5
3
4
5
2
3
6
7
5
H
0
1
1
0
0
0
0
0
0
1
2
1
J
F
M
A
M
J
J
A
S
O
N
D
L
22
19
22
29
30
23
29
26
28
21
16
18
M
9
8
9
1
1
7
2
4
2
8
12
11
H
0
1
0
0
0
0
0
1
0
0
2
1
J
F
M
A
M
J
J
A
S
O
N
D
L
18
17
23
27
30
29
30
29
27
17
15
14
M
9
8
8
3
1
1
0
1
3
12
10
14
H
3
3
0
0
0
0
1
1
0
0
5
2
North West
South West
Does this summary provide evidence to help answer with Q1? If so, what is it?
Does this summary provide evidence to help answer with Q2? If so, what is it?
Sci. Info Skills
Summary 6 - Daily Comparison of Readings Between Regions
The values in these graphs are the number of days where a particular sub-region has the highest/higher
value that day.
ALL THREE
Pairs of regions
Does this summary provide evidence to help answer
with Q1? If so, what is it?
Does this summary provide evidence to help answer
with Q2? If so, what is it?
Now use this evidence to draw some conclusions.
Variation across the year
Variation across Sydney
What does Summary 6 tell you?
Assignment 3
Download the files (pdf) containing the graphs and questions from the Assignment webpage.