Chapter 3
How to Do Scatterplots and Maps
In SPSS 10.0/11.00
In our case the hypothesis test involves the analysis of bivariate correlation between two
variables. In such cases we advise you to start with making a scatterplot which will make
it possible to see the general relationship between the variables.
To do the scatterplot, go to the menu line and choose:
Graphs → Scatter
You will see the following window:
Chapter 3
Press “Define” button. You will see the following submenu:
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Scatterplots and Maps in Spss
The independent variable should be moved to the X axis, whereas the dependent one
should be placed on the Y axis. The independent variable in our case is
AGRICULTURE- CONTRIBUTION TO LOCAL FOOD SUPPLY. Thus, let us move it
to the X axis. The dependent variable is FIXITY OF SETTLEMENT. Thus, we are to
move it to the Y axis. But first we have to find it. To do this we would advise you to look
in your notes and to see what is this variable number (Do you remember we asked you to
write it down?). This number is 61. The total number of variables in the database is just a
bit smaller than 2000. Hence, our variable should be quite close to the beginning of the
list (note that if its number were, say, 1700, you would have to move to the end of the
list). In general, knowing variable number facilitates greatly to find the variable. That is
why we advised you to write down variable numbers when you find them in the
Codes.doc file.
Finally, we have put AGRICULTURE- CONTRIBUTION TO LOCAL FOOD SUPPLY
to the X axis. FIXITY OF SETTLEMENT is on the Y axis. Now we can press the OK
button. And we shall the following scatterplot:
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Chapter 3
7
6
5
4
3
2
1
0
0
1
2
3
4
5
6
7
Agriculture-Contribution to Local Food Supply
In fact, in this form the scatterplot is not particularly informative. In order to make it
really informative you will have to edit it. To do this, first double click on the scatterplot
(the time between two clicks should be VERY small – otherwise you will not simply get
in the editing mode). You will see the following:
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Scatterplots and Maps in Spss
Now, first enlarge the SPSS Chart Editor window and choose in the SPSS Chart Editor
menu line:
CHART → OPTIONS
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Chapter 3
You will see the following:
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Scatterplots and Maps in Spss
Now tick “Show sunflowers” and “Fit Line: Total”, and then press “Fit Options” button.
You will see the following:
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Chapter 3
Mark “Lowess.” Press “Continue”, then “OK”, and the scatterplot will be changed in the
following way:
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Scatterplots and Maps in Spss
Diagram 3.1.
We have changed the scatterplot in two important ways. First, we did “sunflowers.” In
the present scatterplot a single circle denotes one case, a circle with two “petals” denotes
two cases, a circle with three “petals” denotes three cases etc.
The other new feature is that a Lowess curve was fitted into the scatterplot. The Lowess
line corresponds to a formula describing the relationship between the variables most
closely, hence, it is sensitive not only to linear, but also to curvilinear relationships. As
we shall see below, this is immensely important for us.
In general, the scatterplot in its current form suggests that we have all the grounds to
expect to find a rather strong and significant correlation between the variables. However,
note that in fact it tells us much more than this. For example, we may notice that in the
reliance on agriculture range 1-3 (that is, 0-10% reliance on agriculture) the growth of
agricultural contribution to food supply does not tend to increase the settlement fixity.
Yet, the growth of reliance on agriculture over 10% (the transition from value 3 to 4 of
the X axis scale) apparently leads to a sharp increase in settlement fixity. This sharp
increase continues with the transformation of agriculture into the most important single
food supplier (even before it starts contributing more than 50% of food – this corresponds
to the transition from value 4 to 5 of the X axis scale). However, the further growth of the
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Chapter 3
agricultural contribution to food supply does not result in as a sharp increase in settlement
fixity (corresponding to the transition from value 5 to 6 of the X axis scale).
(Incidentally, how to get to know what all these 2, 4, or 6 mean? It is very simple. You
should not just close the “Codes.doc” while working in the SPSS with the Standard
Sample database. There you can easily find answers to all such questions.
To understand why we advise you to start your analysis of correlation with building a
scatterplot, let us make a scatterplot for two variables: political complexity and polygyny
For the latter we shall use v860. It is named “Cultural Basis of Polygyny”, but has the
following values:
1 = Monogamy prescribed
2 = Monogamy preferred, but exceptional cases of polygyny
3 = Polygyny preferred by individual men with leadership attributes (chiefs, medicine
men, outstanding hunters)
4 = Polygyny preferred by men of a higher social class: men of wealth, rank, nobility, etc.
5 = Polygyny preferred by most men, and attained by most men of sufficient years or
wealth to obtain wives.
Hence, it may well be regarded as a polygyny index.
Now, follow the algorithm specified above. If you do not do any mistakes the result will
look as follows:
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Scatterplots and Maps in Spss
Diagram 3.2.
6
5
4
3
2
1
0
0
1
2
3
4
5
6
Jurisdictional Hierarchy Beyond Local Ccommunity
The scatterplot immediately suggests that the relationship between political complexity
and polygyny is curvilinear. The polygyny level tends to increase with the growth of
political complexity up to a medium complexity level (3 = 2 political integration levels
over community, which corresponds to complex chiefdoms and their equivalents [e.g.
complex tribal confederations). However, afterwards it tends to decrease rather sharply.
Normal correlation tests (like Pearson r, or Spearman’s Rho ones) are only aimed at
analysis of linear relationships. Hence, in our case such tests would yield patently
misleading results. That is why we advise you so strongly to make scattergrams before
doing any crosstabs and statistical tests.
For an exercise now do a scatterplot for population density and political complexity. If
you do not do any mistakes, the result should look as follows:
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Chapter 3
Diagram 3.3.
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5
4
3
2
1
0
0
1
2
3
4
5
6
7
8
Population Density
Interpret now the scatterplot.
Note that using the "Scatter" option you can also do maps. This makes much sense, as
before studying correlations between cultural traits it is very helpful to study the
geographic distribution of traits in question. Let us, for example, make a map specifying
the geographic distribution of postmarital residence patterns. To do this map (and other
maps) use file S-DATMAPnew.sav. After opening it choose the "Scatter" option. Move
"Latitude" to Y Axis; move "Longitude" to X Axis. Move "Marital Residence" (v69) to
"Set Markers by" box.
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Scatterplots and Maps in Spss
Press "OK". You will see the following:
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Chapter 3
80
Marital Residence
60
*
40
Neolocal-separate fr
om kin
20
Ambilocal-w / either
w ife's or husband's
0
Patrilocal or virilo
cal
-20
Avunculocal-w /husban
d's mother's brother
-40
Matrilocal or uxoril
-60
ocal-w ith w ife's kin
-200
-100
0
100
200
Longitude in Degrees
In fact, it is possible to get to know much using even this map. However, such maps
produced directly by SPSS are not really user-friendly. So we would advise you to edit it.
To do this double click on the map. Imagine that we would like to study the patterns of
geographic distribution of matrilocal vs. patrilocal residence. So click on a matrolocal
residence marker (within the map itself, or in its margin), then choose in the SPSS Chart
Editor menu line:
FORMAT → MARKER
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Scatterplots and Maps in Spss
You will see the following:
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Chapter 3
We would advise you to choose the dark circle and the large size by clicking at the
respective options:
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Scatterplots and Maps in Spss
Now click "Apply". As a result the map will experience the following change:
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Chapter 3
Now do the same with the patrilocality markers. The map will now look sa follows:
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Scatterplots and Maps in Spss
Next, we would advise you to change a bit the colours. To do this choose in the SPSS
Chart Editor menu line:
FORMAT → COLOR
Click on the markers whose colors you would like to change, select color you prefer and
click "Apply". Some general advice. If you are going to use the map in your essay, thesis
etc., which will be printed out with a black-and-white printer, it would make sense to
observe the following points. Avoid light colors – printers frequently fail to print them
out (sometimes they are not visible even in Powerpoint presentations). We would advise
you the following colors which could look satisfactorily both in multicolor and blackand-white formats: dark-blue for continent contours, red for one marker, dark-grey for the
alternative marker. After changing the map this way it will look as follows:
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Chapter 3
80
Marital Residence
60
*
40
Neolocal-separate fr
om kin
20
Ambilocal-w / either
w ife's or husband's
0
Patrilocal or virilo
cal
-20
Avunculocal-w /husban
d's mother's brother
-40
Matrilocal or uxoril
-60
ocal-w ith w ife's kin
-200
-100
0
100
200
Longitude in Degrees
In fact, we would still advise you to make some further amendments to this map. One of
the points is that in our case the marker labels are too long. It would make sense, for
example, to shorthen the first label from "Neolocal – separate from kin" to just
"Neolocal". To do this double-click on any marker legend and you will see the following:
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Scatterplots and Maps in Spss
Using this menue you could make any changes you like of both legend title and marker
labels. Just do not forget after making changes to any label click the "Change" button
(otherwise your changes will be lost). Finally click OK. Now the map will look as
follows:
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Chapter 3
80
60
40
Residence
20
*
0
Neolocal
-20
Ambilocal
Patrilocal
-40
Avunculocal
-60
Matrilocal
-200
-100
0
100
200
Longitude in Degrees
Finally, it might make sense to delete the axis titles ("Longitude in Degrees" and
"Latitude in Degrees") – we do not really need them (to do this just double-click on the
respective axis title, delete it in the opened window and press OK). The final version of
the map will look as follows:
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Scatterplots and Maps in Spss
80
60
40
20
Residence
0
*
Neolocal
-20
Ambilocal
Patrilocal
-40
Avunculocal
-60
-200
Matrilocal
-100
0
100
200
Now we can easily interpret the map. We see immediately that in the world of traditional
cultures the dominant postmarital pattern was patrilocal. The matrilocal residence
occurred much more rare, and most matrilocal cases concentrate in South-East Asia and
adjacent part of Oceania, and eastern parts of both North America and South America.
Note that this immediately suggests that the observed distribution of these cultural traits
might be to a considerable extent a result of diffusion processes (and hence, we are
confronting here what cross-cultural anthropologists call "Galton Problem" [on which see
below in Chapter *]).
Now make a map of geographical distribution of matrilineal vs. patrilineal descent. To do
this use variable DESCENT - MEMBERSHIP IN CORPORATE KINSHIP GROUPS (v70). If you
follow correctly the algorithm specified above, you will get the following map:
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Chapter 3
80
60
40
20
Descent
0
*
Bilateral
-20
Ambilineal
Patrilineal
-40
Double
-60
-200
Matrilineal
-100
0
100
200
Now try to interprete this map (Suggestion: a meaningful interpretation of this map could
be done most easily if you compare it with the map of geographic distribution of
postmarital residence patterns above).
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Scatterplots and Maps in Spss
After this let us move further.
To test a correlation we would advise you to use a cross-tab option.
Thus, let us move to our next chapter.
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