Statit Custom QC Graphics
In addition to variable and attribute charts, Statit provides the following.
Frequency Charts
 Pie Chart. Displays several values,
each as a slice of a pie. Each slice may be
labeled what percentage of the total pie it
represents.
 Bar/Line Charts. Display one or more
sets of Y values in relation to a single X
value. Statit allows a wide variety of attributes
for individualBar/Line Items to be controlled.
Statit supports 7 different styles of Bar/Line
charts:
 Bar Chart. Displays vertical
or horizontal bars next to each other.
 Area Chart. Plots one or more
variables with the area between the X
axis and the values filled in, creating
a colored, shaded or pattern filled area.
 Curve (spline) Chart. Plots a
fitted curve through each value in the
variable.
 Line Chart. Plots one or more
variables in a fashion similar to that
of an Area Chart, but without the filled
area beneath the plot.
 LoWeSS (Locally Weighted Scatterplot
Smoother) Chart. Plots values for
a variable with a robust smoothed curve
fitted to the values added.
 Point Chart / Scatterplot. Plots
the values of a variable as individual
points on the chart.
 Trend Chart (linear regression).
Plots the values of a variable and overlies
a "trend" line.
 XY Chart. An XY chart typically plots
one or more Y values against a single X value.
Statit allows up to 6 unique X values to each
be plotted against a corresponding unique
Y value. There are three types of XY charts:
 Point Chart / Scatterplot. Plots
one or more XY pairs of variables on a
single chart, showing each pair as an
individual point in the plot.
 Line Chart. Plots one or more
XY pairs of variables on a single chart,
with each plot shown as a connected line.
 Curve (spline) Chart. Plots one
or more XY pairs of variables on a single
chart, with each plot shown as a smoothed
spline curve running through the points
in the plot.
 Histogram. Plots a histogram for
measurement variables.
 Box Plot. Displays a box plot for
each variable in the variable list. The procedure
requires a real variable and can handle a
grouping variable that is numeric or string.
 Probability Plot. Display a normal
probability plot for a single variable. The
purpose of this plot is to show whether the
data approximates a normal distribution, which
can be an important assumption in many statistical
analyses.
 QQ Plot. Examines the distribution
of one variable or compares the distributions
of two variables. It may be used to generate
any one of three types of plots:
 Percentile plot
 Percentile Comparison
 Empirical QQ Plot
 XY and Contour Plots:
 XY Plot. Displays a single variable
on the X axis and one or more variables
on the Y axis. The default XY plot produced
is a scatter plot. Each point in the graph
is identified by a marker symbol. Where
there are multiple Y variables, a different
marker is used for each Y variable. An
XY plot may also have the points connected;
these are called curve plots.
 XYZ Plot. Displays a scatter
plot where a classification variable is
used to determine groups for a single
Y variable. Each of these groups will
be plotted as a separate Y variable, up
to a maximum of 12 groups.
 Bubble Plot. Displays a single XY plot
with the marker symbol size based on a
response variable. The marker symbol is
always a circle.
 Sunflower Plot. Is useful when
both the X and Y variables are categorical
and the response variable contains counts
or frequencies. The values of the response
variable are represented by petals—a
single point is represented by a dot.
 Contour Plot. For each point
(x, y) in equallyspaced grid of points
in the XY plane, a representative value
of z is computed by local smoothing (fitting
a local quadratic regression). Then a
contour plot is made representing the
relation of these computed zvalues to
(x, y) points in the grid.
 Scatterplot Matrix. Displays scatter
plot matrices, that is, all variables in the
list are plotted against each other. This
makes it easy to track an interesting point
or group of points from plot to plot. An optional
smooth curve can be drawn through each scatterplot
to help visualize the relationship between
the two variables.
 Function Contour Plot. Displays contour
plots of a mathematicallydefined relation
Z = f(X,Y), as opposed to a contour plot for
empirical data. The plot is drawn in a manner
that represents threedimensional relationships
in two dimensions. Lines or areas in the plot
represent levels of magnitude, Z, corresponding
to a position (X,Y) on a plane.
