StatCrunch Creating Scatter Plots Video Lecture - Statcrunch Tutorials

in this video you will learn to create
scatter plots using statcrunch the data
set I will be using is called the asking
prices for four-bedroom homes and
College Station Texas this data set was
collected in order to compare
four-bedroom homes listed for sale in
two adjoining cities Bryan Texas and
College Station Texas using a real
estate website fifteen homes were
randomly selected from four bedroom
homes listed for sale and Bryan and 15
homes randomly selected from four
bedroom homes listed for sale and
College Station the square footage
column contains the square footage for
each home and the location column lists
the city where the home is located the
price column contains the asking price
for the home and thousands of dollars so
for example the first home in the data
set has an asking price of 2 million
$400,000 or 2.4 million dollars this is
reflected in the data set as 2400 to
quickly adjust the asking prices in the
data sets of dollars simply add three
zeros to the values shown let's begin by
constructing a scatter plot for square
footage and price to do so under the
graph menu choose scatter plots in the X
column choose square footage and in the
Y column choose price I'll click compute
notice that there is a clear outlier it
can be identified by clicking and
dragging the mouse around the point the
row containing the Associated value is
highlighted in the data table in this
case the outlier is in the first row
this highlighting can be cleared by
using the Clear button in the lower left
hand corner outliers can have a large
impact on the graphics as they may
greatly expand the range of one
more of the axes obscuring the details
in the plot to remove the outlier in
this example under options choose edit
this takes us back to the original
window where we built our scatter plot
here statcrunch has other options for
the user to choose a where expression
can be used to filter the data values
notice in the scatter plot the outlier
is the only home in the data set with a
price above 2000 or 2,000,000
therefore the outlier can be removed by
only considering homes where price is
less than 2000 so in the where box I'm
going to type in the expression price
less than 2000 note that statcrunch is
case sensitive so when you type in an
expression it needs to appear the exact
same way as in the data table I'll click
compute and now I get an updated
scatterplot shown without the outlier to
compare the nature of the relationship
between the square footage and the
asking prices across the two cities of
Bryan and College Station Texas the
points in the scatter plot can be
color-coded according to the location of
each home to do so back under options
choose edit in the group by box I'm
going to choose location I'll click
compute and the resulting scatter plot
shows the homes and bryant in blue and
the homes and College Station and red in
many cases it is desired to examine a
best fitting function that characterizes
the relationship between the two
variables statcrunch allows for
overlaying the best fitting polynomial
up to the 4th order to do so back under
options choose edit I am going to
overlay a line so
under overlay polynomial order box I am
going to choose one to overlay a
polynomial of order one or a line of
best fit I'll click compute the
resulting scatter plot shown shows the
best fitting line for Brian and blue and
the best fitting line for College
Station in red the equation of each line
can be obtained by double-clicking on
the lines in the plot
you