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Getting Familiar With JMP 8


Title: Getting Familiar with JMP 8 Author: Arun Last modified by: Arun Created Date: 1/22/2009 9:33:06 PM Document presentation format: On-screen Show (4:3) – PowerPoint PPT presentation

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Title: Getting Familiar With JMP 8

Getting Familiar With JMP 8
  • Dr. Andy Mauromoustakos

Welcome to JMP 8 workshop
  • JMP is statistical discovery software that can
    help you explore data, fit models, discover
    patterns, and discover points that dont 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
  • With a progressive structure, you build context
    that maintains a live analysis, so you dont 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.

Welcome to JMP 8 Workshop
  • 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 management tools for sorting and combining
  • a calculator for each table column to compute
  • a facility for grouping data and computing
    summary statistics
  • special plots, charts and communication
    capabilities for quality improvement
  • tools for moving analysis results between
    applications and for printing
  • a scripting language for saving frequently used

Data Table Features
  • Start JMP software
  • Open a JMP data table
  • Identify key data table features

Starting JMP
  • To begin using JMP software, double click on the
    icon corresponding to either
  • the JMP application
  • or
  • 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
Open a data table
  • From the JMP menu bar
  • From the JMP Starter File Menu
  • Now browse the folder and select the JMP data
    file and click open

JMP Starter Preferences
  • 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.

JMP Starter Preferences
  • Now let us activate the Laser Pointer in the
    Reports option under the Preferences.
  • The Laser Pointer is now active and you can use
    it when you point the figures in the JMP output
    as shown below.

JMP Starter (1 of 12) File Menu
JMP Starter (2 of 12) File Menu
JMP Starter (3 of 12) File Menu
JMP Starter (4 of 12) File Menu
JMP Starter (5 of 12) File Menu
JMP Starter (6 of 12) File Menu
JMP Starter (7 of 12) File Menu
JMP Starter (8 of 12) File Menu
JMP Starter (9 of 12) File Menu
JMP Starter (10 of 12) File Menu
JMP Starter (11 of 12) File Menu
JMP Starter (12 of 12) File Menu

Opening a Data Table
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
Opening a Data Table
Data Type
The data type of a column determines the way the
data can be used. JMP uses two primary data
Numeric Columns with numbers that can be used in
calculations. These data are right-aligned. (see
Depth or BD).
Character 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).
Modeling Type
The modeling type of a column determines how the
data are used in an analysis. 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).
Modeling Type
  • To specify or see the modeling type of a
  • Right-click on the column heading and choose
  • 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
Column Role
  • 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.

Column Role
  • To specify the column role of a variable
  • Right-click on the column
  • heading.
  • Choose Preselect Role from the given options.
  • Specify a role from the drop-down menu.
  • More on consequences on Preselecting Column Roles

Data Table Features
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 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) Press the Ctrl key to select
nonadjacent rows (columns) Note The ALT key is
the OPTION key...
Menu Headings (1 of 2)
  • 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 variables)
  • DOE facilitates the Design Of the Experiment

Menu Headings (2 of 2)
  • 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 operations
  • Help accesses the main help features in JMP

File Menu
  • 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 current)
  • Saves the script of the executed analysis.
  • Saves the executed analysis and data table as a
  • exits JMP software

Edit Menu
  • 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 image
  • pastes data
  • Uses the first line of information on the
    clipboard as column headers
  • clears the data at the end of the current data
  • selects all data in data table
  • saves selection in desired format
  • runs script if there is one in the current
  • Submits the JMP scripts as a SAS program to SAS

Edit Menu
  • 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
  • Lets you edit or manipulate the report before you
  • 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

Tables Menu
  • 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.

Rows Menu
Recall that JMP treats rows as
  • excludes or includes an observation in
    statistical analyses
  • 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 (default20)
  • moves selected rows (defaultTo End)
  • deletes selected rows
  • Lets you select rows, create subsets and animate
    selected rows

Cols Menu
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 conditions
  • use this columns values to identify points in
  • locks column into left-most position in the data
  • hides columns from view
  • excludes variable in analysis role assignment
  • modifies the attributes of selected columns
  • lets you move columns by several options
  • deletes selected columns
  • Lets you quickly recode data that is coded

DOE Menu
The Design of Analysis menu launches
statistical platforms.
  • Create a design tailored to meet specific
  • 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 settings.
  • Lets you define a set of factors that are
    ingredients in a mixture
  • Creates a design by spreading the design points
    out to the maximum distance possible between two
  • 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
  • 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.

Analyze Menu
The Analyze menu launches statistical
  • investigates the distribution of values in each
  • investigates all types of pairwise
    relationships and analysis
  • models one or more response variables with one
    or more predictor variables
  • allows for the creation of a model specific for
    the data
  • 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

Graph Menu
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

Graph Menu
  • 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
  • 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
  • The Custom Profiler command is available for
    tables with columns whose values are computed
    from model prediction formulas.

Tools Menu (1 of 3)
The Tools menu (below) and the toolbar (right)
contain several tools for manipulating analysis
  • 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.

Tools Menu (2 of 3)
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
  • 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
  • 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.

Tools Menu (3 of 3)
  • 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.

View Menu
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 projects.
  • 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 them.
  • 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 edge.

Windows Menu
  • 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 command.
  • creates a duplicate data table (or analysis
  • 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

Help Menu (1 of 2)
  • To access the main help features from the help
    menu in JMP.
  • Select Help ? Contents to obtain the main help
  • Inspect the help dialog.

Help Menu (2 of 2)
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
Data Table Management and Analysis
  • 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

Managing the Data Table
  • Inspect the file. Lets utilize
    Standardize Columns Attributes to appropriately
    place the units information which is presently
    included as part of the Ksat variable names.

Managing the Data Table
  • Now lets 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
  • Select Cols ? Column Infoand 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

Managing the Data Table
  • 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
  • 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

Managing the Data Table
  • 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
  • Change the name of the MLRA column to Major Land
    Resource Areas.
  • Click once on the column heading (selects the
    column) for MLRA in the column panel.
  • Click again on your selected word MLRA to edit
  • Type Major Land Resource Areas.
  • 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.
  • Change the name back to MLRA.

Cursor Forms
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
Data Validation
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).
Transforming Data
  • Create new variables from existing ones to
    facilitate the analysis
  • Use the Formula editor to create and change
    formulas that create the column values

Transforming Data Using the Formula Editor
  • 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 Editor.
  • To view the formula that created the column
  • Select lksat-g by clicking it the column panel.
  • Right-click the selected column, and see that
    Formula is checked.
  • 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.

Transforming Data Using the Formula Editor
  • Lets create a new variable that is the natural
    logarithm of Ksat-arit.
  • Select Cols ? New Column
  • Note the defaults (Name, Data Modeling Type)
    in the New Column window.
  • Select Column Property ? Formula. (See how the
    Formula Editor window opens.)
  1. Select Transcendental ? Log
  2. Select Ksat-arit (from the Table Columns). Note
    that it appears in the box as shown at the right.
  3. Select OK to close the Formula box.
  4. Select OK to close the New Column.
  5. To delete the new Column 31 option, select it and
    click on Delete Columns.

More on Formula Editor
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 observations? Hint One
can use several ways to accomplish this task
three of which are sketched below. 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.
More on Formula Editor
  • 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 before)
  • 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

Useful Columns Operations
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 them. 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 MOVE SELECTED COLUMNS.
Current Selection
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.
Useful Rows Operations
  • 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
  • Select Rows ? Clear Row States
  • Now to get it back the way it was
  • Select Rows ? Color or Mark by Column.
  • Select Soils.
  • Mark the box Set Marker by Value (as shown).
  • Select OK.
  • To save all changes to the row states of
  • Select File ? Save
  • Note This will be used in the rest of the slides
    unless otherwise indicated.

Data Table Operations
  • 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),
  • Select Tables ? Sort ( Fill the entries as shown
    below by clicking on the column names in the
    appropriate order.)
  • Select Sort.
  • In the resulting data table (Untitled),
    MLRA116 appears first since by default the
    sort works in ascending order.
  • Now click and drag the mouse to select the first
    10 observations (SoilsCaptina).
  • Select Tables ? Subset
  • Click OK

Selecting Subsets of Data Using Select Where
  • Suppose that we are interested in the following
    subset of the data that meets ALL three criteria.
  • Texture class contains l for loam,
  • Acidic pH samples (pHlt5)
  • With Iron greater than 100 (Fegt100)
  1. Use Rows? Row Selection? Select Where
  2. Select Texture Class from the drop down list
  3. Select the condition equals from the drop down
  4. Enter I in the adjacent field
  5. Click on Add condition which will show you
    Texture class equals I
  6. Click OK

Creating Summary Statistics
To calculate and tabulate the median and range
values for NO3, P and K for each soil. 1. Select
Tables ? Summary.
2. Click OK. Summary statistics will appear in
a new spreadsheet
3. Double click on Source to get Table property
Using the Data Filter (1 of 3)
  • 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.

Using Data Filter (2 of 3)
  • 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
  • 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
  • The Start Over button removes all the filter
  • Now left click on the value of Texture Class I.

Using Data Filter (3 of 3)
  • 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 lt sign.
  • Similarly, to add the variable Fe gt100, 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 lt.

Creating One-Way Comparisons
One-way ANOVA Fishers LSD
To calculate the means Ph levels and test for
equality of the mean Ph levels for different soil
types -- especially to compare Bowies 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.
Detecting relationships and outliers in many
To investigate Bivariate and Multivariate
relationships among WRs.
Select Analyze ? Multivariate Methods
? Multivariate
Click OK to get a Scatterplot Matrix. Click on
the red triangle for more analysis options.
Contingency Tables and Correspondence Analysis
To investigate the relationship of Texture Class
to Soils.
Analyze ? Fit Y by X
Click OK
Analysis and Graphs Creating, Saving, and
  • To investigate the relationship of Nitrogen to
    Carbon for four selected soils (MLRA134)
    (Note Use the data table
  • Analyze ? Fit Y by X
  • Nitrogen ? Y, Response and Carbon ? X, Factor ?
  • Click on the red triangle by Bivariate and
    select Group By ? Soils
  • Click on the red triangle by Bivariateagain and
    select Fit Line

Discuss the details for customizing getting the
graph printed or pasted
Distributions and EDA
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)
CDF Plot and more EDA
To get the detailed distribution of Na for each
soil across the soil profile Analyze ? Fit Y by
Click OK to get distributions. Click on red
triangle for more analysis options.
Matched Pairs Analysis
To determine if the the mean Ksat-arit is
significantly greater than the mean Ksat-geo
Analyze ? Matched Pairs
Click OK to get
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)
Creating Summary Plots Using Chart
To review the relationship of Water Retention
(WRs) to Depth at different pressures for each
Graph ? Chart
Choose Data.
Choose line chart
Creating Summary Plots Using Control Chart
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
Creating Summary Plots Using Variability Chart
To study amounts of NO3, P, and K across the
profile for each soil
Graph ? Variability Chart
Creating Summary Plots Using Pareto Chart
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 customize
Creating Summary Plots Using Ternary Plot
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 MLRA
  • Drag and drop sand under Mean
  • Drag and drop silt under sand
  • Drag and drop clay under silt
  • To show a graph which goes hand-in-hand with the
  • Click the Platform Menu
  • Select Show Graph
  • To make the created table into a data table
  • Click the Platform Menu
  • Select Make Into Data Table

Graph Builder
  • Graph builder functionality allows you make a
    graph in just few drag and drops. We could say
    Graph Builder is Graphical Version of Tabulate
  • Open ARsoils
  • To Launch the Graph Builder Platform
  • Click Graph Menu Graph Builder
  • To visualize how the Bulk Density (BD) change
    over Depths for different soils,
  • Drag and Drop Depth in X
  • Drag and Drop BD in Y
  • Drag and Drop Soils in Wrap
  • To add a smoother to the graph

Bubble Plot
  • Bubble Plot allows you to Visualize your data in
    more than 3 dimensional Space.
  • 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
  • Click Save as Flash (.SWF)

Scripting (JSL)
  • 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
  • packaging - when you need to create a new user
    interface to do a set of things.
  • data manipulation - when you need to manipulate
    data in complex ways
  • simulation - when students and researchers need
    to simulate statistical processes.
  • record keeping - when you want to save the
    commands for how you analyzed
  • customization of graphs - you can put scripting
    code inside of graphs that executes each
    time the graph is drawn to overlay additional
    graphic elements.

Scripting (JSL)
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. Run the vbball.jsl script that creates
visual summary basketball statistics.
Scripting Summary
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 scripts.
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
panel. You can access, edit and change each
variables information through the Column Info
dialog. Select the variable and click on
ColsColumn Info... From the Column Info
dialog, you can change a variables name, data
type, and modeling type, as well as do column
validation (list or range checks), add notes,
units, specification limits, etc. 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.
Practice using Jim Goffs Heating.xls
  • 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
  • Name the stacked column (by stacking the last
    three columns), Temp and name Method the new
    column that indicate the heating method (similar
  • Explore the data and plot them using things
  • you learned so far

Analysis Summary Comments
  • The Analysis process should
  • Identify the data source and create the data
  • 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 further.
  • 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 first.

JMP 8 Summary
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