Making a Scatterplot
A scatterplot gives a visual picture of the relationship of (usually)
two continuous variables. One can also use Likert-scaled variables in
a scatterplot. Pick two variables that can be seen as an explanatory
(independent) variable and a response (dependent) variable. Draw a
Graphs/Legacy Dialogs/Scatter/Simple Scatter
) so that the
dependent variable goes to the Y axis and the independent variable
goes to the X axis. Interpret the resulting scatterplot.
Add a regression line to the finished figure by first entering the chart editor by double clicking the chart, and then selecting the
plots in the figure by clicking them and selecting
Chart/Add Chart Element/Fit Line at Total/Fit Method: Linear
. What conclusions you can draw from the scatterplot?
If it appears that there is a linear dependency between your chosen
variables, compute the correlation between the variables
). What does the correlation
coefficient tell you? Is the correlation between the variables
Correlation and Statistical Significance
Go back to (or redo) the correlation matrix made in day 3, and write a short
analysis on its correlation coefficients and their statistical significance.
Draw a scatterplot with a regression line and compute the correlation
coeffiecient for the
variables “Country’s cultural life undermined or enriched by immigrants”
(imueclt) and “Year of birth” (yrbrn). How do you interpret the correlation
Preparing Graphs and Tables for Reports
Pick a graph or a table you made before, and make it fit for
publishing. Use the following guidelines (adapted from Maarit
, especially for crosstabulations):
Only display row, column OR cell percentages in your tables, but
don’t use the %-character. Usually there’s no need to display cell
Display the figures, where the percentages are counted from,
i.e. row and column sums and their total sum. If the reader is
interested in cell frequencies, he/she can count them utilizing the
A good way to make sure that the percentages are displayed
correctly is to attempt to explain the central conclusion of the
table. An example from a study regarding reading as a hobby: “88% of
adults in Narujärvi, and 32% of adults in Uppojoki read at least 3
novels each year.” (It would be considerably more awkward to state the
percentage of people reading novels coming from Uppojoki.)
Avoid displaying too much decimal numbers, they make your graphs
Display the sum of percentages, that is a row or column of 100s,
either in the right or bottom marginal depending on the direction of
the counted percentages.
The meaning of a variable’s categories must be explicated
clearly. Usually the variable value (i.e. the category “number”) is
not enough, but each category should have a description in the
table. This is easily done by giving the variable value labels in the
Variable View. If the category descriptions don’t fit in the table,
further explications can be situated in the footnotes.
The table title should be informational, and additional
descriptions can be written in the footnotes if needed.
should be able to understand the table’s contents without looking for
explanations from the report’s text proper.
The title does not
need to be smart nor snappy, this being a scientific report. An
example of a title: The distribution of Finnish women aged 18 to 35
years in income categories in the year 1997.
- The table source is written in the lower margin of the table.
Repeating the figures and details from the table excessively in
the report’s text is a sure way of making the reader lose
- A table needs to have a number in addition to a title.
When dealing with a table of percentages, the number of
observations should be clearly displayed.
The best tip: Show your tables and graphs to a friend who’s not
afraid to speak out, and ask her to tell you what the tables are
about, and what conclusions one can make from the figures.