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JMP® 9 - Quick Guide

Instructions presume an open data table, default preference settings, and appropriately typed, user-specified variables of interest.

RMC = Click Right Mouse Button

Download the JMP 9 Quick Guide

Graphing
Frequency Distribution Analyze > Distribution (For categorical variables, frequencies are displayed. Otherwise, quantiles and moments are.)
Bar Chart
  1. Graph > Graph Builder > Drag Continuous Variable to Y and Categorical to X > RMC > Points > Change to > Bar
  2. Graph > Chart
Pie Chart Graph > Chart > Options > Pie Chart
Histogram Analyze > Distribution
Stem and Leaf Plot Analyze > Distribution; select  Stem and Leaf
Scatter Plot 2D
  1. Graph > Graph Builder > Drag Continuous Variable to Y and another one to X
  2. Analyze > Fit Y by X (Bivariate)
  3. Graph > Overlay Plot
Scatter Plot 3D Graph > Scatterplot 3D
Scatter Plot Matrix
  1. Graph > Scatterplot Matrix
  2. Analyze >  Multivariate Methods > Multivariate
Trellis Plot Graph > Graph Builder > Drag Column to Y and one to X; Drag Nominal or Ordinal Column to Wrap
Line Chart
  1. Graph > Graph Builder > Drag Continuous Variable to Y and another one to X > RMC in graph > Smoother > Change to > Line
  2. Graph > Overlay Plot; select  y options > Connect Thru Missing
Box Plot - One Level
  1. Graph > Graph Builder > Continuous column to Y > RMC (Right Mouse Click) > Points > Change to > Box Plot
  2. Analyze > Distribution
Box Plot - Two or More Levels
  1. Graph > Graph Builder > Continuous column to Y and categorical to X > RMC > Points > Change to > Box Plot
  2. Analyze > Fit continuous Y by categorical X; select  Display Options > Box Plot
Basic Statistics
Descriptive statistics
  1. Analyze > Distribution; (basic stats are shown by default; to see more select  Display Options > More Moments
  2. Tables > Summary
  3. Tables > Tabulate
z- or t- test
  1. 1-Sample
  2. 2-Sample
  1. Paired t
  1. Analyze > Distribution; select  Test Mean
  2. Analyze > Fit Y by X; select  t Test or Means/ANOVA/Pooled t
  3. Analyze > Matched Pairs
Testing Proportions (make 0/1 indicator Nominal or Ordinal)
  1. 1 Proportion
  2. 2 Proportions
  1. Analyze > Distribution; select  Test Probabilities
  2. Analyze > Fit Y by X
Contingency table – Chi-Square test Analyze > Fit Y by X (both X and Y must be categorical)
Covariance Analyze > Multivariate Methods > Multivariate; select  Covariance matrix
Correlation
  1. Analyze > Multivariate Methods > Multivariate
  2. Analyze > Fit Y by X > Density Ellipse
Test for Normality/Goodness-of-fit Analyze > Distribution; select  Continuous Fit > Normal; select  by Fitted Distribution > Goodness of Fit
Probability/Random Variables
Probability Variables On data table select  Columns > New Column; RMC on new column > Formula; select Probability from Functions Window; select desired probability function. Note: For more information on the expected parameters see help under Probability Functions
Random Variables
  1. On data table select  Columns > New Column; RMC on new column > Column Info; Click on drop down box next to Initialize Data > Random
  2. On data table select  Columns > New Column; RMC on new column > Formula; select Random from Functions Window; select desired Random function.

Note: For more information on the expected parameters see help under Random Function
Distribution Fitting Analyze > Distribution; select  Continuous Fit, then select desired distribution(s).
Analysis of Variance
One-Way Analyze > Fit Y by X; select  Means/Anova (Y must be continuous; X categorical)
Two or more Factors Analyze > Fit Model
Randomized Blocks Analyze > Fit Y by X; include a categorical column in Block role
Multiple Comparison Methods Analyze > Fit Y by X; select  Means/Anova; select  Compare Means
Test for Equal/Unequal Variances Analyze > Fit Y by X; select  Means/Anova; select  Unequal Variances
Regression
Scatter Plot Analyze > Fit Y by X (Bivariate)
Simple Least Squares
  1. One Variable
  2. One or More Independent Variables
  1. Analyze > Fit continuous Y by continuous X; select  Fit Line
  2. Analyze > Fit Model
Logistic Regression
  1. One Variable
  2. One or More Independent Variables
  1. Analyze > Fit categorical Y by continuous X; select  Fit Line
  2. Analyze > Fit Model
Multiple Regression Analyze > Fit Model
Stepwise Regression Analyze > Fit Model > Personality – Select Stepwise
Residual Analysis
  1. Analyze > Fit Model; Run Model; select  Row Diagnostics
  2. Analyze > Fit Y by X; select  and choose a fit; select  from fit report and “Save Residuals” or “Plot residuals”
Interaction Plots Analyze > Fit Model with interaction effects; Run Model; select  Factor Profiling > Interaction Plots
Durbin-Watson Test Analyze > Fit Model; Run; select  Row Diagnostics > Durban Watson Test
Nonparametric techniques
Wilcoxon Rank Sum Test Analyze > Fit Y by X; select  Nonparametric > Wilcoxon Test
Fishers Sign Test (for 2x2 tables only) Analyze > Fit categorical Y by categorical X
Wilcoxon Signed Rank Sum Test Analyze > Distribution on continuous X; select  Test Mean > Check Wilcoxon Signed Rank Box
Kruskal-Wallis Test Analyze > Fit continuous Y by categorical X; select  Nonparametric > Wilcoxon Test
Spearman’s p Analyze > Multivariate Methods > Multivariate; select  Nonparametric Correlations > Spearman’s p
Time Series
Time Series Plot Analyze > Modeling > Time Series
Moving Averages Analyze > Modeling > Time Series; select  ARIMA
Exponential Smoothing Analyze > Modeling > Time Series; select  Smoothing Models
Holt-Winters Method Analyze > Modeling > Time Series; select  Smoothing Model > Winters Method
Data Mining
Decision Trees Analyze > Modeling > Partition
Clustering Analyze > Multivariate Methods > Cluster
Neural Networks Analyze > Modeling > Neural
Logistic & Multiple Regression Analyze > Fit Model
Quality Control
Control Charts
  1. Run Chart
  2. X-bar
  3. Individual Measurements (IR)
  4. P Chart
  5. U Chart
  6. CUSUM
  1. Graph > Control Chart > Run Chart
  2. Graph > Control Chart > XBar
  3. Graph > Control Chart > IR
  4. Graph > Control Chart > P
  5. Graph > Control Chart > U
  6. Graph > Control Chart > CUSUM
Pareto Graph > Pareto Plot
Cause & Effect Diagram Graph > Diagram
Variability Chart Graph > Variability/Gauge Chart
  1. Capability
  2. Capability with additional graphs on same output
  1. Graph > Capability
  2. Graph > Control Chart > IR; check Capability Box.  > OK, Fill in Specification Limits
Design of Experiments (DOE)
Factorial Design
  1. DOE > Full Factorial Design
  2. DOE > Screening Design
Screening Design DOE > Screening Design
Response Surface Design DOE > Response Surface Design
Sample Size and Power Calculations DOE > Sample Size and Power

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