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Scatter Plots
7:09Scatter plots are the best plot to use if you are interested in showing relationships between data and seeing trends between two variables.
A scatter plot is used to find
correlations between two variables in
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a dataset.
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Scatter plots are the best plot to
use if you're interested in showing
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relationships between data and
finding trends.
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By plotting one variable on the x-axis and
the other on the y-axis, a scatterplot
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can show us how much correlation, if any,
exists between the two variables.
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The question I have is: for all of
the Caribbean countries in a given year,
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let's say 2020, is there a correlation
between total population and total GDP?
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Is GDP greater when
populations are greater?
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Let's start by filtering our worksheet
to show only data from 2020.
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In cell B1 for year click on the filter
icon to open the filter menu.
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In the section Filter by values,
click Clear.
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This will uncheck everything
in the values window below.
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In the values window,
scroll down and select 2020.
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Then click OK.
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Now our spreadsheet only shows data for
the year 2020.
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Awesome.
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For our scatter plot, we need two columns.
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First, click the header for
column C to select all the values for
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all the countries' populations.
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Then while holding the Command
key on Mac or the Ctrl key on PC,
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click the header for column E to select
the total GDP for all countries.
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Now we are ready to insert a chart
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My suggested chart was a scatterplot,
lucky for me.
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If yours is a different chart type,
go to the chart editor and
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select scatter plot from
the chart type drop down menu
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Let's customize the chart so
we can gain more insights.
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First, let's edit the title to be
more descriptive and centered.
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Double-click on the chart title to open
the chart editor and edit the text.
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I'll say that this is GDP total versus
population in the Caribbean for
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the year 2020.
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And once again, I'll center the text
by clicking on the drop down below.
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Editing the title of the chart is
usually one of the first steps I do when
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customizing, because it sets a clear
expectation of what the data represents.
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If I'm working with multiple charts,
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it becomes more important to keep
everything distinct from each other.
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So as for our data,
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notice how there are many data points
at the bottom left of the chart.
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Those points represent
the smallest countries, and
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they all have small economies.
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As we look over to the right of the chart,
there's the kind of spread for
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the countries with larger populations,
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and it's a little unclear what
exactly the correlation is.
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We can use a trend line to find out
if there is a correlation at all.
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In the chart editor's customize tab,
click on the Series section.
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This is where you can customize the look
of the points on the scatter plot,
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but what I'm looking for
here is a series of checkboxes.
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I'll scroll down and
I'll click on the checkbox for
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trendline, and it draws
a line through the data points.
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The line represents the relationship
between all the points of data.
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Notice how it goes between some
data points, but not all of them.
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That's okay.
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The trendline is not supposed
to be a perfect fit, it's just
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the best fit possible that represents
the correlation between the data.
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There is another way we can make
this correlation more clear.
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I'll scroll down in the chart editor and
click this checkbox to show R squared.
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What is R squared?
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R squared is a statistical measurement
that describes the meaning of
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the trendline.
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It measures the correlation
between two variables.
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In our dataset, those variables
are population size and total GDP.
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I'll leave some resources about R
squared in my Teacher's Notes below.
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For now, there are three things that you
need to know about R squared that will
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help you right away.
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First, an R squared value that is closer
to positive 1 means that there is a strong
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positive correlation
between the two variables.
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Both variables increase or
decrease at the same time with each other.
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Second, a value closer to negative 1
means that there is a strong negative
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correlation.
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When one variable increases,
the other variable decreases.
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Third, a value close to 0 means that
there is a very weak correlation
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between the two variables, and
maybe no relationship exists.
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So, our value is positive 0.558,
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which can be interpreted as
a somewhat moderate correlation.
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The trendline's direction shows a positive
correlation between countries' populations
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and their total GDP.
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In general, as population increases,
so does GDP.
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Let's make sure to include that
information in our Alt text.
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Open the Alt text menu and
copy the title over.
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For our descriptive analysis,
there is a moderate positive correlation
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between population and total GDP for
Caribbean countries in 2020.
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Generally, as population increases,
so does the countries' GDP.
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Remember, you can copy and
paste my titles and
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descriptions for these alt texts
in the Teacher's Notes below.
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Now, let's move this
chart to its own sheet,
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and rename the sheet.
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I'll call this one
Caribbean 2020 Scatter Plot.
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Now it's your turn again.
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Create another scatter plot for another
year to find the correlation between
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population and total GDP for the Caribbean
countries, then add a trendline.
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Remember to add your alt text before
moving your chart to a new sheet.
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You can also find my example
in the Teacher's Notes below.
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When you're ready,
I'll catch you in the next video.
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