Getting Familiar with JMP 8 by fjhuangjun

VIEWS: 225 PAGES: 92

									   JMP® is statistical discovery software that can help you explore
    data, fit models, discover patterns, and discover points that don’t fit
    patterns. As statistical discovery software, the emphasis in JMP is to
    interactively work on data to find out things.
    • Using graphics, you are more likely to make discoveries. You are also
      more likely to understand the results.
    • With interactivity, you are encouraged to dig deeper, for one analysis
      can lead to a refinement, one discovery can lead to another discovery;
      and you can experiment with statistics to improve your chances of
      discovering something important.
    • With a progressive structure, you build context that maintains a live
      analysis, so you don’t have to redo analyses, so that details come to
      attention at the right time.
   JMP IN, a student version of JMP, is distributed by Duxbury Press.
   JMP is statistical software that gives you an extraordinary graphical
    interface to display and analyze data. JMP is for interactive
    statistical graphics and includes:
    • a spreadsheet for viewing, editing and manipulating data
    • a broad range of graphical and statistical methods for data analysis
    • an extensive design of experiments module
    • options to highlight and display subsets of the data
    • data management tools for sorting and combining tables
    • a calculator for each table column to compute values
    • a facility for grouping data and computing summary statistics
    • special plots, charts and communication capabilities for quality
    • tools for moving analysis results between applications and for printing
    • a scripting language for saving frequently used routines

 Start JMP software
 Open a JMP data table
 Identify key data table features
 •   To begin using JMP software, double click on the icon
     corresponding to either
 •    the JMP application
 •    a JMP data table

The program opens with a brief
animation and soon after a standard
application window with standard
Windows features and controls and the
a new Tip of the Day
   From the JMP Starter File Menu:           From the JMP menu bar:

   Now browse the folder and select the
    JMP data file and click “open”
From the JMP File menu bar select Preferences,
or in the JMP Starter window click on

These choices in the preferences allow you to tailor things such as:
   general operation and appearance of JMP
   background color of windows and graphs
   type, style, and size of fonts
   graphic formats for copy and drag results and RTF and HTML files
   communications settings
   default directory paths for file locations
   results initially presented by each analysis or graph platform.
   settings for importing and exporting data to suit your needs or situation.
Now let us activate the Laser Pointer in the “Reports” option under the

The Laser Pointer is now active and you can use it when you point the figures
in the JMP output as shown below.
Example: The data are stored in the data table.
To open the data table select
Open Data Table from the JMP starter
Select from the “appropriate subdirectory”.

The data table is the entire
window. It contains
• the data grid on the right and
• three information panels on
the left
     • one for the table
     • one for the columns
     • one for the rows
The rows and columns panels
give corresponding counts.

To hide or unhide the three left
panels click on the blue
diamond located on the upper-
left corner of the data grid.
This data table has
• 30 columns (variables) and
• 120 row (observations)
                                            DATA TABLE CURSOR FORMS…
                         MORE ON PANELS AND23
The data type of a column determines the way the data can be used.
JMP uses two primary data types:

Columns with numbers that
can be used in calculations.
These data are right-aligned.
(see Depth or BD).

Columns with numeric and/or
character values that can be
used to designate different
levels of the variable.
These data are left-aligned.
(see Soils).

The modeling type of a column
determines how the data are used in an

Three modeling types used in JMP:

Continuous: For numeric data whose
values are used directly in computations
(for example, BD).

Ordinal: For numeric and/or character
data used to group the observations into
a set of levels with an inherent order
(for example Depth).

Nominal: For numeric and/or character
data used to group the observations into
a set of levels without any inherent
order (for example, MLRA).
To specify or see the modeling type of a
   Right-click on the column heading and
     Column info... from the given options.
   Or, simply double click on the column title.

A new window will open showing
the column specifications.

Discuss current properties, row
states and much more here…

The column role identifies the role of the column in an analysis.
Four column roles used by JMP are:

X         the column stores values for the independent or predictor variable

Y          the column stores values for the dependent or response variable

Weight    the values for the column represent the weight for each row

Freq      the values for the column represent the frequency for each row

If no specific role is identified for the variable, use the “No Role” option.


To specify the column role of a
   Right-click on the column
 Choose Preselect Role from the
given options.
Specify a role from the drop-
down menu.

More on consequences on
Preselecting Column Roles …

                                                                   5   2

Click on the area or box marked
1: to select a row
2: to select a column
3: to deselect all selected rows
4: to deselect all columns
5: to edit a cell              6
6: to change the modeling type
7: to edit the variable column
information (column name, data
and modeling type, format, etc.)
double click

After selecting a row (column):
• Press the Shift key to select a block of adjacent rows (columns) 1
• Press the Ctrl key to select nonadjacent rows (columns)
Note: The ALT key is the OPTION key...                                     29
File     performs most routine file functions, such as opening, closing, and     saving
Edit     performs most common editing functions such as cutting and pasting
Tables   performs table functions, such as sort, subset, and merge
Rows     performs row operations (recall that JMP treats rows as observations)
Cols     performs column       operations(recall    that   JMP   treats   columns    as
DOE      facilitates the Design Of the Experiment

Analyze   performs most statistical analyses

Graph     generates a variety of plots

Tools     displays analysis window tools

View      appears only under the Windows operating system environment

Window    selects among currently opened windows and performs window

Help      accesses the main help features in JMP

• Builds the new data table, new script window, new project
and new Journal
• opens an existing JMP data table
• closes the current JMP data table
• Writes an open text file to a JMP data table
• saves the current data table
• removes all changes to data table since you last saved it
• links to data base at a different location
• Lets you open an internet browser within JMP
• selects default preferences
• printing options
• previews ready to print window
• selects desired print format
• location and name of the data table(s) used (1 is most
• Saves the script of the executed analysis.
• Saves the executed analysis and data table as a Project
• exits JMP software
• undoes the last action if possible
• redoes last action if possible
• cuts selection and keeps it in clipboard
• copies selection
• copies selection only in text format
• Preserves the data table's column labels in the copied
• pastes data
• Uses the first line of information on the clipboard as
column headers
• clears the data at the end of the current data table
• selects all data in data table
• saves selection in desired format
• runs script if there is one in the current window
• Submits the JMP scripts as a SAS program to SAS

   Gives you the ability to find and
    replace text in data tables and scripts

   Finds the line in the data table for
    observations that meet your criteria

   Saves a report just as it appears in the
    report window

   Lets you edit or manipulate the report
    before you save

   Reveals a submenu to customize menus
    and toolbars. Revert to Factory
    Defaults resets the menus and toolbars
    to the arrangement when you first
    installed JMP
 request summary statistics by grouping columns
 subset selected rows. Random sampling
 sort rows by specified columns.
 stack values from several columns into several
rows in one column.
 split a column, mapping several rows on one
column to one row in several columns.
 interchange rows and columns.
 combine rows from several sources.
 join rows from several sources by matching
value a table
 Tabulate- To build table using two option,
interactive or dialog.
 Missing Data Patterns- To find the patterns of
missing values in the data and make a table of each
pattern and its frequency.

     Recall that JMP treats rows as observations.
   excludes or includes an observation in statistical
   hide or unhide an observation in point plots
   labels or unable an observation in point plots
   lists colors
   lists markers
   searches for observations meeting your criteria
   returns to last selection
   utilities on row selection
   undoes all row selection
   assigns colors or markers to rows
   brings up a window useful for browsing all cols for
    each row
   adds new rows (default=20)
   moves selected rows (default=To End)
   deletes selected rows
   Lets you select rows, create subsets and animate
    selected rows
       Recall that JMP treats columns as variables
    creates a new column
    lets you add more than one column at a time
    Highlights a specific column in the table
    opens the column info for a selected column
    lets you assign the most common analysis roles
    lets you define values using some formula
    lets you enter a list of valid values or range limit
    use this column’s values to identify points in plots
    locks column into left-most position in the data grid
    hides columns from view
    excludes variable in analysis role assignment dialogs
    modifies the attributes of selected columns
    lets you move columns by several options
    deletes selected columns
    Lets you quickly recode data that is coded
    The Design of Analysis menu launches statistical platforms.
   Create a design tailored to meet specific requirements.
   Sift through many factors to find the few that have the
    most effect.
   Find the best response allowing quadratic effects
   Generate all possible combinations of the specified factor
   Lets you define a set of factors that are ingredients in a
   Creates a design by spreading the design points out to the
    maximum distance possible between two points
   Lets you create an optimal design for models that are
    nonlinear in the parameters.
   Make inner and outer arrays from signal and noise
   Optimize a recipe for a mixture of several ingredients.
 Add more runs to an existing data table. Replicate, add center points, fold over or
  add model terms.
 Plot any two of the power to detect an effect, the sample size, and the effect size
  given the third. Or, compute one given the other two.                             38
   The Analyze menu launches statistical platforms.
• investigates the distribution of values in each
• investigates all types of “pairwise relationships and
• models one or more response variables with one or
more predictor variables
• allows for the creation of a model specific for the
• performs nonlinear regression, time series analysis
and neural nets analysis
• explores how multiple variables relate to each other,
and how points fit that relationship, cluster and
discriminant analysis
• performs survival analysis

  The Graph menu generates a variety of graphs.
• produces bar and pie charts
• produces overlay plots
• Scatterplot 3D produces a three-dimensional rotatable
display of values from any three numeric columns in the
active data table
• produces contour plots
• Bubble Plot is a scatter plot which represents its points as
circles (bubbles)
• The Parallel Plot command draws a parallel coordinate plot
• Produces a rectangular array of cells drawn with a one-to-
one correspondence to data table values
• The Tree Map command displays tree maps
• The Scatterplot Matrix command allows quick production
of scatterplot matrices
• The Ternary Plot command constructs a plot using
triangular coordinates
• The Diagram platform is used to construct Ishikawa charts,
also called fishbone charts, or cause-and-effect diagrams        40
• produces statistical quality control plots
• Variability or Continuous Gage charts are for responses
  whose values can be measured on a continuous scale.
  Attribute Gauge charts are for responses whose values are
  binary or categorical
• produces Pareto charts
• Capability analysis, used in quality control, measures the
  conformance of a process to given specification limits.
• The Profiler is available for tables with columns whose
  values are computed from model prediction formulas
• The Contour Profiler command works the same as the
  Profiler command
• The Surface Plot command plots surfaces and points in
  three dimensions based on formulas or data
• The Custom Profiler command is available for tables with
  columns whose values are computed from model
  prediction formulas.

         The Tools menu (below) and the toolbar (right) contain several tools for
manipulating analysis windows.

                            Arrow            A default tool used to identify, highlight,
                             and magnify points. It is also used to enhance Click on
                             a point to highlight it. Click and hold on a point to
                             identify the point. Shift-Click to extend a selection
                            Help (Question mark)       To access JMP Help. Select
                             the help tool and then click graphs, plots, or tables to see
                             help windows.
                            Selection        To select cut-and-paste territory from a
                             report. Drag the fat plus cursor. It selects territory
                             according to the hierarchy of the report. Click and drag
                             across the area you want to copy to select and highlight it.
                             Use SHIFT-Click to extend the selection. To unselect
                             click anywhere in the selected area.
                            Scroller        To grab a report and scroll by dragging.
The Tools menu (below) and the toolbar (right) contain several tools for manipulating
analysis windows (discussed in that order below)

    Grabber (Hand)             To direct manipulation in plots
     and charts, e.g., change the # of bars in a histogram or to
     shift the boundaries of the bars on the axis, to spin a
     spinning plot,or to rearrange a scatterplot matrix.
    Brush           Click and drag with the Brush to
     highlight selection. Use alt-click to change the size of
     the brush rectangle. Use shift-click to extend a selection.
    Lasso            Click and drag with the Lasso tool to
     highlight the selection.
    Magnifier        To zoom in on any area of a plot. The
     click-point becomes the center of a new view of the data.
     (Alt-Click to restore the original plot.)
    Crosshairs       A movable set of axes to measure points
     and distances in graphical displays. Useful on a fitted
     line or curve to identify the response (“Y”) value for any
     given value of “X”.                                                          43
The Tools menu (below) and the toolbar (right) contain several tools for manipulating
analysis windows (discussed in that order below)

                           Annotate       To place a text box in a JMP report
                            window. To add notes. To remove a note, drag it off the
                            report window.
                           Line           To draw thin, thick, or dashed lines which
                            can have arrows on the ends.
                           Polygon        To draw any shaped polygon.       May be
                            spline smoothed.
                           Simple Shape To draw either oval shapes or rectangles.
                            May be filled or raised for a three-dimensional effect.

      The View menu appear only under the Windows operating system environment.
   JMP Starter      Opens the JMP Starter Window.
   Window List          The Window List command displays a
    pane at the left side of the JMP window that lists the name
    of each window you have open in JMP
   File System          The File System command displays a
    pane at the left side of the JMP window that shows your
    PC's file system
   Projects              The File System command displays a
    pane at the left side of the JMP window that lists all open
   Log                   Displays a pane that monitors JSL statements as they execute.
    (The log window is editable.)
   Show Toolbars        Lists all available toolbars with a check box to hide or reveal
   Float Log              To detach or re-attach the log window to the bottom of the
    screen, right-click Log and select Float Log Window
   Status Bar           Turns the Windows status bar on or off at the bottom window
          The Window menu helps you organize the windows produced during a JMP
session. All open windows generated in a session are listed in the Bring to Front

                            creates a duplicate data table (or analysis window)
                            closes all windows of same type
                            closes all windows
                            organizes windows within JMP (tile..)
                           redraws active window
                           the Font Sizes command gives you a quick way to
                          change the font size JMP uses
                           moves active window behind all other
                           changes the name of an active window
                           hides current window
                           displays a list of all hidden windows
                           lists all open windows at preset

To access the main help features from the help menu in JMP.
Select Help  Contents to obtain the main help reference.
Inspect the help dialog.

For example, to access help on the topic of neural nets:
Select Help  Index type Neural Net and double click on Neural Net from the index

     Edit the data table
     Inspect and edit column information
     Use list check and range check validation.
     Transforming data (Create new variables)
     Sorting the data.
     Creating subsets of the data.
     Creating and plotting summary statistics
     BY-Group Analysis
     More EDA using to explore
      various objectives and demonstrate analysis and
      graphs features.
Inspect the file. Let’s utilize “Standardize Columns Attributes” to
appropriately place the units information which is presently included as part of the
Ksat variable names.

   Now let’s edit the variables of both
    Ksat columns by taking out the units
    from the names and editing the Notes
    placeholder for the Ksat-geo to reflect
    that it is a geometric and not an
    arithmetic mean.
   Select both Ksat variables. (if not
    already selected)
   Select Cols  Column Info…and delete
    the (cm/hr) from both Column names
    OR right-click on each column heading
    then select Column Info
   Select Column Properties Notes and
    edit the notes box for Ksat-geo
   Select OK

   Now let us edit the variables of
    both “Ksat-” columns by taking
    out the units from the names and
    editing the Notes placeholder for
    the Ksat-geo to reflect that it is a
    geometric and not an arithmetic
    mean again.
   Select both Ksat variables. (if
    not selected)
   Option click (right hand mouse)
     Standardize Attributes …
   Under Format Best  select
    Fixed Dec
   Change the default from 0 decimals to 4 in the Dec: area for that format
   Select OK
   Save the data as select File  Save As…

Column names can be up to 31 characters long and can consist of any combination
of letters and numbers, as well as special symbols (and a blank(s)).
Change the name of the MLRA column to Major Land Resource Areas.
1. Click once on the column heading (selects the column) for MLRA in the
   column panel.
2. Click again on your selected word MLRA to edit it.
3. Type Major Land Resource Areas.
4. You can adjust the column width if necessary by placing the cursor over the
   dividing line on the right side of the column you want to widen. As the cursor
   moves over the line, it changes from an arrow to a double-arrow.
5. Change the name back to MLRA.

JMP software has a graphical user interface (GUI). The cursor changes when
it passes over certain areas of a data table. Depending on the data table, you
most commonly see
The cursor is the standard arrow when it is in the panels area to the left of the
data table, in the triangular rows and columns area in the upper-left corner of
the data grid, or on the title bar of the tables panel

When the cursor is within a column heading or a row number area, it becomes
a large plus, indicating it is available to select rows or columns

When you select editable text, the cursor becomes a standard I-beam

The cursor changes to a double arrow when it is on a column boundary

when the cursor is over a column with list check validation

when the cursor is over a column with range check validation

The cursor changes to a pointer over any red triangle icon or diamond-shaped
disclosure button                         54
Data validation enables you to set up a table of acceptable values or range of values
for a column. JMP supports two types of validation accessible through the Column
Info… dialog.

List check          is commonly used for character variables to ensure all values
                    entered for a column correspond to values in a validated list.

Range check         is available only for numeric variables to ensure all values
                    entered are within a specified range of values.

Close the Column Info… dialog and return to the data table.
Move the cursor over the desired column panel. Right Click and then select validation
in the drop down list. Which columns are employing validation?
Answer: BD (is range checked) and Texture class (is list checked).

   Create new variables from existing ones   to facilitate
  the analysis
   Use the Formula editor to create and change formulas
  that create the column values

First let us inspect the last variable in the column panel.
The       next to a column name indicates that this column is created by the Formula
To view the formula that created the column:
1. Select lksat-g by clicking it the column panel.
2. Right-click the selected column, and see that Formula… is checked.
3. Select Formula and you see that the variable is created to be the natural logarithm
      (Log10 is used for log base 10) of the ksat-geo variable.

Let’s create a new variable that is the natural
     logarithm of Ksat-arit.
1. Select Cols  New Column…
2. Note the defaults (Name, Data & Modeling
     Type…) in the New Column window.
3. Select Column Property  Formula. (See how
     the Formula Editor window opens.)

4.   Select Transcendental  Log
5.   Select Ksat-arit (from the Table Columns).
     Note that it appears in the box as shown at the
6.   Select OK to close the Formula box.
7.   Select OK to close the New Column.
8.   To delete the new Column 31 option, select it
     and click on Delete Columns.

Say we are interested in creating as a new column the sum of the Sand, Silt and Clay
variables. We want the new variable to be the total of the three variables and give it a
Format with 0 decimals. Does the new variable contain the value of 100 for all
Hint: One can use several ways to accomplish this task three of which are sketched

Method 1: Highlight to select the three variables one at a time from the Column
variables and click the plus in between selections. Your formula should look “like the
one below” before you click Apply
                                   sand + silt + clay
Select the outside box that contains the above expression and press the delete Key, or
simply click on the Clear button.

Method 2: Double click inside the no formula and using your keyboard type the above
  expression and then click Apply (you should see the same formula in the box as
Select the outside box that contains the above expression and press the delete Key, or
   simply click on the Clear button.
Method 3: From the Functions menu select Statistical  Sum (press the comma from
  your keyboard twice to create two commas that will receive each of the three
  variables from the Table Columns that now reads Sum(sand,silt,clay). Click Apply.
Delete the new variable when you are finished.
MORE on boxing and a tour of the functions in the Formula Editor…
Quickly review some other useful columns operations
such as: Label, Scroll Lock, Hide and Exclude and
Move (Reorder) columns. The results of all these
actions is shown on the right
Label/Unlabel : Make MLRA into a label column…
Scroll Lock/Unlock (column name in italics at the
column panel): Select the Soils variable and select
Cols Scroll Lock. Note that Soils appears in italics in
the column menu. Observe that Soils remained
viewable on the data grid even though we are
displaying the last two chemical properties next to
Hide/Unhide : Hide/ the middle three WR-’s.
Exclude/Unexlude      : Exclude the Ksat-arit from
graphing and analysis. That particular variable and the
top surface observations are seen as been excluded
from consideration ….
Reorder Columns: Select the variable you want to
move and right click on it, then choose REORDER
COLUMNS from the Drop down list and then select
There are several ways to select rows (observations):
Click in the left margin next to the row number.
Click at the start of the selection and drag to the opposite end.
Click at the start of the selection and shift-click at the opposite end.
Control-click to extend the selection without including rows in between.
Control-click to deselect a row.
Use the Row Selection command in the Rows menu and the Select Where... option
to select rows that meet a criterion or a set of criteria.

The same operations are used to select columns (variables) as well.

Quickly review the rows panel to see the top surface
observations for each of the 12 soils are marked as excluded
and that each observation from a given soil has its own color
and marker assigned (that are used in all graphs…). You can
do to rows some other useful operations similar to the
columns operations discussed in the previous slide such as:
Label, Hide and Exclude. We will concentrate here on
Colors, Markers, and Color or Mark by Column to review
how we assigned the row states in the
The results of all these actions are shown on the right (either
from the Rows panel or the Rows menu).
1. Select Rows  Clear Row States
     Now to get it back the way it was:
2. Select Rows  Color or Mark by Column.
3. Select Soils.
4. Mark the box Set Marker by Value (as shown).
5. Select OK.
6. To save all changes to the row states of
7. Select File  Save as…
Note: This will be used in the rest of the slides unless
otherwise indicated.
Usually one can obtain a great deal of
information by sorting the data.If, for
example, you are primarily interested in
all the data from MLRA “116” (NWA),
1. Select Tables  Sort ( Fill the entries
      as shown below by clicking on the
      column names in the appropriate
2. Select Sort.
In the resulting data table (“Untitled”),
MLRA=“116” appears first since by
default the sort works in ascending order.
Now click and drag the mouse to select
the first 10 observations (Soils=Captina).
1. Select Tables  Subset
2. Click OK

Suppose that we are interested in the following subset of the data that meets ALL three
  a)Texture class contains “l” for “loam”,
  b)Acidic pH samples (pH<5)
  c)With Iron greater than 100 (Fe>100)
1. Use Rows Row Selection Select
2. Select Texture Class from the drop
   down list
3. Select the condition “equals” from the
   drop down list
4. Enter “I” in the adjacent field
5. Click on “Add condition” which will
   show you “Texture class equals I”
6. Click “OK”
To calculate and tabulate the median and range values for NO3, P and K for each
1. Select Tables  Summary.

2. Click OK. Summary statistics will appear in a new spreadsheet
3. Double click on Source to get Table property window

   The Data Filter command in the Rows menu gives a variety of ways to
    identify subsets of data Using Data Filter commands and options, you
    interactively select complex subsets of data, hide these subsets in plots, or
    exclude them from the analyses.
   Select Rows       Data Filter
   To use the Data Filter, select one or more variables (Here it is texture class)
    in the Add Filter Columns list whose values you want to use as filters and
    click Add.

Data Filter Control Panel:
   The values of the variables you chose are in boxes in the lower part of the panel.
   Above the variable are three check boxes that determine the display modes of the
    values you select.
   The Clear button at the top of the panel clears all selections you have made.
   the large plus button at the bottom of the panel opens the Add Filter Columns list
    again at any time so that you can add variables to the filter process.
   The Start Over button removes all the filter columns
   Now left click on the value of Texture Class “I”.

   Now click on the plus button at the bottom of the panel to add variable pH
    to the filter.
   Now to select the all the observations less 5 on pH, Shift + click on the
    right side less or equal to symbol to get < sign.
   Similarly, to add the variable Fe >100, click + button at the bottom and in
    the list of variables select Fe. Now to select the observations greater than
    100, Shift + Click on the left side less than or equal to symbol to get <.
                         One-way ANOVA Fisher’s LSD
To calculate the means Ph levels and test for equality of the mean Ph levels for
different soil types -- especially to compare “Bowie’s” pH with the other soils’ pH.
     Analyze  Fit Y by X

 Click OK to get the plot.
 To choose other options,
click on the red triangle.
 To investigate Bivariate and Multivariate
 relationships among WR’s.
  Select Analyze  Multivariate Methods
                  Multivariate

Click OK to get a Scatterplot Matrix.
Click on the red triangle for more analysis options.
MORE …                                                 71
To investigate the relationship of Texture
Class to Soils.
 Analyze  Fit Y by X

                                   Click OK

MORE …                                        72
To investigate the relationship of Nitrogen to Carbon for four selected
soils (MLRA=“134”) (Note: Use the data table
Analyze  Fit Y by X
Nitrogen  Y, Response and Carbon  X, Factor  OK
Click on the red triangle by Bivariate… and select Group By…  Soils
Click on the red triangle by Bivariate…again and select Fit Line


                                                              Discuss the details
                                                              for customizing
                                                              getting the graph
                                                              printed or pasted

   Distribution is a powerful Exploration tool. To demonstrate, use the general soil
   texture and composition of the Captina soil found in NWA.
   Select Analyze  Distribution

And after you Click on Captina (to select it) …

To get the detailed distribution of Na for
each soil across the soil profile:
Analyze  Fit Y by X

Click OK to get distributions. Click on red
triangle for more analysis options.
To determine if the the mean Ksat-arit is
significantly greater than the mean Ksat-geo
           Analyze  Matched Pairs

                                            Click OK to

Note the “unsualy high” difference in the
two Ksat values for Row 11

       Good place here to use the magnifier tool …(and ALT to return…)
To review the relationship of Water Retention
(WR’s) to Depth at different pressures for each soil:
 Graph  Chart            Choose Data.


                                    Choose line chart
MORE…                                               77
To review the “pH Process” (for stability, consistency) over consecutive batches,
create a Control Chart (Shewhart) of pH for every “Batch” (10 consecutive samples)
from the same soil.
Graph  Control Chart


 MORE…                                          78
To study amounts of NO3, P, and K across the profile for each soil:
Graph  Variability Chart


 MORE…                                             79
To examine for differences in Texture class for each soil by MLRA:
Graph  Pareto Plot


           Part of output shown here. Show how to use Layout to
 To examine for differences Texture class for each soil by MLRA.
  Graph  Ternary Plot


Note only the first level (Bowie) of the BY group shown…
Take time here to show how to save the script into the data table…
To summarize and get the means for sand, silt & clay with respect to each soil
and MLRA

  Tables Tabulate
  Drag and drop “MLRA” into “Drop
  Zone for rows”
  Drag and drop “Mean” into “N” to
  replace N with Mean

• Drag and drop “Soils” after
• Drag and drop “sand” under
• Drag and drop “silt” under “sand”
• Drag and drop “clay” under “silt”
• To show a graph which goes hand-
in-hand with the table
     • Click the Platform Menu
     • Select “Show Graph”
• To make the created table into a
data table
     • Click the Platform Menu
     • Select “Make Into Data
• Graph builder functionality allows you
make a graph in just few drag and drops. We
could say Graph Builder is Graphical
Version of Tabulate function.
• Open ARsoils
• To Launch the Graph Builder Platform
    • Click “Graph” Menu           “Graph
• To visualize how the Bulk Density (BD)
change over Depths for different soils,
    • Drag and Drop “Depth” in X
                                              • To add a smoother to the graph
    • Drag and Drop “BD” in Y
    • Drag and Drop “Soils” in Wrap

• Bubble Plot allows you to Visualize
your data in more than 3 dimensional
• Open
• To Launch a Bubble plot platform,
• Click “Graph” Menu    “Bubble Plot”
• Provide variables as shown below to
make a bubble plot & click OK.

                                        • Click “Go” to visualize the data.
                                        • To Save it as a flash movie
                                              • Click on the platform menu
                                         85   • Click “Save as Flash (*.SWF)
Scripting is considered an advanced feature that is not for novice users. The
principal needs that scripting addresses are:

production jobs - when you are doing the same sequence of work repeatedly.
customization - when JMP doesn't have a built-in feature and you need to
program it
packaging - when you need to create a new user interface to do a set of
data manipulation - when you need to manipulate data in complex ways
simulation - when students and researchers need to simulate statistical
record keeping - when you want to save the commands for how you
analyzed something.
customization of graphs - you can put scripting code inside of graphs that
executes each time the graph is drawn to overlay additional graphic elements.

     Illustrate the use of scripts by executing various scripts in the Table panel of
     1. Select Ternary Plot in the column window and left click on the red diamond
           and select Edit to view the Script for the ternary plot
     2. Select Ternary Plot in the column window and left click on the red diamond
           and select Run Script.

Demonstrate the use of scripts by running the OnewayLines.JSL script to create
letters and annotate the Fit Y by X output (see slide 59).
If time permits demo two more scripts…
Test_for_correlated_variances_comparison.jsl tests using Dr. Meullenet sensory
data.                                                  87
      Run the vbball.jsl script that creates visual summary basketball statistics.
A JMP script is an concise set of instructions that you can use to achieve the same
results you achieve when you issue a series of interactive commands.

A JMP script conveniently performs otherwise tedious work, provides a record and
documentation for review, and alleviates unintentional deviations. You can easily
and quickly repeat analyses using a script.

Scripts can be saved to the data table, script window, or file. You can attach scripts
to the Toolbar with a user-specified button or to the users menu.

Scripts are used to extend existing JMP capabilities or to create entirely new
capabilities as seen in the two cases on the previous slide. Finally, live
demonstrations (as in vbball) and animated results can be created using JMP

JMP software stores information in a data table. For purposes of analysis, JMP views
each row as a single observation and each column as a single variable.

Date type is indicated by the alignment of data within a column. Numeric variables
(numeric values that can be used in calculations) are right-aligned. Character variables
(numeric and/or character values that designate different levels of a variable) are left-
aligned. Modeling type is included to the left of each variable name in the Column

You can access, edit and change each variable’s information through the Column
Info… dialog. Select the variable and click on Cols¸Column Info... From the Column
Info… dialog, you can change a variable’s name, data type, and modeling type, as well
as do column validation (list or range checks), add notes, units, specification limits,

If you are working with a data table that has many columns and observations, but you
are only interested in a few variables, subset the data you need to make those
observations and variables of interest into a new data table.

Use the Heating.xls and try to read the data as a Excel file.
    (Use the File Open and remember to select the appropriate File of Type extension
    in that Dialog window. Create a table property that has the notes about the data
    using JimGoff_Heatdata.txt (his email txt file), add units to the variables and
    save the “Multivariate version of the data in a JMP file. (Now see to make sure
    that is “similar” to

Now use Tables Stack to create a “univariate” version.
    Name the stacked column (by stacking the last three columns), “Temp” and name
    “Method” the new column that indicate the heating method (similar to

Explore the
           data and plot them using things
        you learned so far…


The Analysis process should
       Identify the data source and create the data table
       Arrange and Transform data if necessary
       Visually mine the data to discover structure
       Fit models and draw conclusions
To analyze complex data always start with exploring the data for outliers trends
relationships before proceeding with the analysis. Remember to always plot a
summary of either all the data or some summary measures to help and guide you
Remember to always start by analyzing and graphing “homogeneous” and smaller
sections of the data by employing the BY feature of each analysis or graph platform

JMP is easy to learn. Statistics are organized into logical areas with appropriate
graphs and tables which helps you find patterns in data, outlying points, or fit
models. Appropriate analyses are defined and performed for you, based on the
types of variables you have and the roles the play.

JMP offers descriptive statistics and simple analyses for beginning statisticians and
complex model fitting for advanced researchers. Standard statistical analysis and
specialty platforms for design of experiments, statistical quality control, ternary
and contour plotting, survival and time series analysis provide the tools you need
to analyze data and see results quickly.


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