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JMP® 8 Student Edition - Quick Guide

Instructions presume a data table is open and the user will specify the appropriate variables of interest.

For complete information and tutorials, please refer to the Using JMP Student Edition handbook available under “Help > Books”.

Graphing
Frequency Distribution	Analyze > Distribution
Bar Chart	Graph > Graph Builder > Drag Continuous Variable to Y and Categorical to X > RMC > Points > Change to > Bar Graph > Chart
Pie Chart	Graph > Chart > Options > Pie Chart
Histogram	Analyze > Distribution
Stem-and-leaf display	Analyze > Distribution; select  Stem and Leaf
Scatter Plot 2D	Graph > Graph Builder > Drag Continuous Variable to Y and another one to X Analyze > Fit Y by X (Bivariate) Graph > Overlay Plot
Scatter Plot 3D	Graph > Scatterplot 3D
Line Chart	Graph > Graph Builder > Drag Continuous Variable to Y and another one to X > RMC in graph > Smoother > Change to > Line Graph > Overlay Plot; select  y options > Connect Points
Box Plot - One Level	Graph > Graph Builder > Continuous column to Y > RMC > Points > Change to > Box Plot Analyze > Distribution
Box Plot - Two or More Levels	Graph > Graph Builder > Continuous column to Y and categorical to X > RMC > Points > Change to > Box Plot Analyze > Fit Y by X; select  Display Options > Box Plot

Basic Statistics
Descriptive statistics	Analyze > Distribution; select   Display Options > More Moments Tables > Summary Tables > Tabulate
z- or t- test 1-Sample 2-Sample Paired t	Analyze > Distribution; select  Test Mean Analyze > Fit Y by X; select  t Test or Means/ANOVA/Pooled t Analyze > Matched Pairs
Testing Proportions (make 0/1 indicator Nominal or Ordinal) 1 Proportion 2 Proportion	Analyze > Distribution; select  Test Probabilities Analyze > Fit Y by X
Contingency table – Chi-Square test	Analyze > Fit Y by X
Covariance	Analyze > Multivariate Methods > Multivariate; select  Covariance matrix
Correlation	Analyze > Multivariate Methods > Multivariate
Test for Normality Test/Goodness-of-fit Test	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	On data table select  Columns > New Column; RMC on new column > Column Info. Click on Drop down box next to Initial Data Values > Random 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 either Normal, LogNormal or Weibull

Analysis of Variance
One-Way	Analyze > Fit Y by X; select  Means/Anova
Two or more Factors	Analyze > Fit Model
Randomized Blocks	Analyze > Fit Y by X; include 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) Graph > Overlay
Simple Least Squares One Independent Variable One or More Independent Variables	Analyze > Fit Y by X; select  Fit Line Analyze > Fit Model
Logistic Regression One Independent Variable One or More Independent Variables	Analyze > Fit Y by X; select  Fit Line Analyze > Fit Model
Multiple Regression	Analyze > Fit Model
Stepwise Regression	Analyze > Fit Model > Personality – Select Stepwise
Residual Analysis	Analyze > Fit Model; Run Model; select  Row Diagnostics
Interaction Plots	Analyze > Fit Model; Run Model; select  Factor Profiling > Interaction Plots
Durbin-Watson Test	Analyze > Fit Model; Run; select  Row Diagnostics > Durban Watson Test

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

Nonparametric techniques
Wilcoxon Rank Sum Test	Analyze > Fit Y by X; select  Nonparametric > Wilcoxon Test
Fishers Sign Test (for 2x2 tables only)	Analyze > Fit Y by X
Wilcoxon Signed Rank Sum Test	Analyze > Distribution; select  Test Mean > Check Wilcoxon Signed Rank Box
Kruskal-Wallis Test	Analyze > Fit Y by X; select  Nonparametric > Wilcoxon Test
Spearman’s P	Analyze > Multivariate Methods > Multivariate; select  Nonparametric Correlations > Spearman’s P

Quality Control
Control Charts X-bar Individual Measurements (IR) p Chart u Chart CUSUM	Graph > Control Chart > XBar Graph > Control Chart > IR Graph > Control Chart > P Graph > Control Chart > U Graph > Control Chart > CUSUM
Pareto	Graph > Pareto Plot

Design of Experiments (DOE)
Factorial Design	DOE > Full Factorial Design 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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