Tutorial

★ wanayoo — archive 1999 http://www.itl.nist.gov/div898/software/dataplot.html/tutorial.htm

Plotting
X-Y Plots: Line Plot Character Plot Scatter Plot Bar Plot Error Bar Plot Vector Plot	Distributional Plots: 4-Plot (sequence plot, lag plot, histogram, normal probability plot) Histogram Bi-Histogram Frequency Plot Rootogram Stem and Leaf Plot Pie Chart Probability Plot Probability Plot Correlation Coefficient Plot Normal Plot Box-Cox Homogeneity Plot Box-Cox Linearity Plot Box-Cox Normality Plot Percent Point Plot Quantile-Quantile Plot Symmetry Plot	Time Series: Run Sequence Plot Lag Plot Auto-, Cross-, Partial Correlation Plot Spectral Plot Complex Demodulation Plot Periodogram Allan Variance Plot Allan Standard Deviation Plot
3-D Plots: 3-D Plot Contour Plot	Multivariate Plots: Andrews Plot Parallel Coordinates Plot Profile Plot Star Plot Symbol Plot Biplot	Design of Experiments and Analysis of Variance Plots Block Plot Box Plot DEX Scatter Plot DEX Mean Plot DEX SD Plot DEX Range Plot DEX Effects Plot
Statistics Plots: Mean Plot Standard Deviation Plot Statistic Plot Bootstrap Plot Jacknife Plot Homoscedasticity Plot Phase Plot Fractal Plot Pareto Plot Analysis of Proportions Plot	Quality Control Plots: XBAR Control Chart S Control Chart R Control Chart C Control Chart U Control Chart P Control Chart NP Control Chart	Reliability, Extreme Value Plots: Tail Area Plot Weibull Plot CME Plot

Data Analysis
Data and Function Transformations: Define variables, and parameters, transform data User Defined Functions Statistical Calculations Mathematical Calculations (interpolation, derivatives, integrals, and more) Matrix Calculations Built-In Functions	Statistical Summaries and Tests: Summary Statistics Runs Analysis Tabulate counts, means, standard deviations, and ranges of grouped data Tabulate counts, means, standard deviations, ranges, or compute the chi-square test of independence for data grouped by 2 variables Confidence Limits for the mean 1- or 2-sample t-test 2-sample F-test 1-sample chi-square test for standard deviations k-sample Bartlett test for homogeneity of variances	Fitting (Regression) and Smoothing: Linear Fitting (Regression) Non-Linear Fitting Exact Rational Fitting Locally Weighted Least Squares Smoothing Weighted Least Squares Fitting Robust Fitting (Iteratively Re-weighted Least Squares, Least Absolute Deviations) Spline Fit Smoothing (Least Squares, Robust)
Experiment Design and Analysis of Variance: Analysis of Variance Median Polish (robust ANOVA) Yates Analysis Principle Hessian Directions for a Yates Analysis	Time Series: Discrete Fast Fourier Transform	Multivariate: Variance-Covariance Matrix Correlation Matrix Principle Components Singular Value Factorization Other Matrix Operations Fisher's Discriminant Analysis Canonical Correlation Analysis

Experiment Design
Monitoring:	Comparative:	Screening:
Optimization: