Cursusprogramma STATGRAPHICS 2018

Onderstaand wordt per cursus aangegeven wat er wordt besproken.

Elke cursus heeft de duur van 1 dag en kan op locatie worden gegeven. Cursusdata in overleg. Vraag ons naar de mogelijkheden.

Introduction:

Data Management

Spreadsheet Data Editor
Assigning Column Names and Types
Entering the Data
Saving and Printing a Data File
DataBook Properties
Importing Data from Other Programs
Querying Databases

Running Statistical Procedures

Data Input Dialog Boxes
Analysis Windows
Analysis Options and Pane Options
Printing Analysis Windows
Page Setup
Using the StatAdvisor
Copying Tables and Graphs to Word and PowerPoint
Using the StatReporter
Selecting Analyses with the StatWizard
Using SnapStats

Manipulating Data

Expressions and Transformations
Data Generators
Sorting Data
Recoding Data

Using StatFolios

Saving Your Session
Loading Saved StatFolios
Start-Up Scripts
StatPublish
Polling Data
Setting System Preferences

Graphics Operations

Changing the Graph Size and Position
Changing Background Colors
Changing Titles and Axis Scaling
Modifying Points and Lines
Setting a New Default Profile
Adding Text
Point Identification
Brushing a Scatterplot
Jittering Points
Smoothing a Scatterplot
Excluding Points
3-D Rotations
Using the StatGallery


Statistics

One Sample Analysis

Summary Statistics
Frequency Tabulations
Frequency Histograms
Percentiles
Quantile Plot
Normal Probability Plot
Stem-and-Leaf Display
Box-and-Whisker Plot
Confidence Intervals
Hypothesis Tests
Testing for Outliers

Distribution Fitting

Tests for Normality
Selecting Alternative Distributions
Goodness-of-Fit Tests
Tail Areas
Critical Values
Transforming Data to Achieve Normality

Comparing Two Samples

Comparison of Standard Deviations
Comparison of Means
Comparison of Medians
Multiple Box-and-Whisker Plots
Quantile-Quantile Plots
Paired Sample Comparisons

Analysis of Attribute Data

Tabulation
Barcharts and Piecharts
Crosstabulation
Mosaic Plots and Skycharts
Contingency Tables
Tests for Association

Comparing Multiple Samples

Summary Statistics
ANOVA Table
Means Table
Means Plot
Multiple Range Tests
Variance Check
Residual Plots

Curve Fitting

Fitting a Straight Line
Plotting the Fitted Model
Regression Statistics
Lack-of-Fit Tests
Selecting a Nonlinear Model
Analyzing Residuals

Multiple Regression

Model Specification
Regression Analysis Table
Stepwise Variable Selection


Fundamentals of Statistical Process Control

This module covers the use of STATGRAPHICS for basic SPC (Statistical Process Control).

Outline: Pareto Analysis

The Pareto Principle
Pareto Charts
Combining Small Classes

Process Capability Analysis for Variables

Selecting the Proper Distribution
Estimating DPMO
Estimating Capability Indices
Calculating the Sigma Quality Level
Non-Normal Capability Indices
Using Tolerance Limits to Set Specifications

Basic Control Charts

Variables Charts for Subgroup Data
Variables Charts for Individuals Data
Attributes Control Charts
Control Charts for Non-Normal Data

Repeatability and Reproducibility Studies

Setting up a Standard Variables Study
Estimating Repeatability and Reproducibility
Average and Range Method vs ANOVA Method
Short Studies.


Advanced Statistical Process Control

This module continues the discussion of using STATGRAPHICS for SPC.

Outline:
Process Capability Analysis for Attributes

Defects (binomial and hypergeometric)
Defects per Unit (Poisson and negative binomial)

Gage Linearity and Accuracy

Setting up a Standard Study
Estimating Bias
Estimating Linearity

Gage Studies for Attributes
Risk Analysis Method
Analytic Method
Signal Theory Method

Advanced Control Charts

Moving Average, EWMA and CuSum Charts
Multivariate Control Charts
ARIMA Charts for Autocorrelated Data
Toolwear Charts for Trending Data
Acceptance Control Charts for High Cpk Processes
Using CuScore Charts to Detect Specific Signals


Introduction to Design of Experiments Using STATGRAPHICS

This module introduces users to the use of STATGRAPHICS for DOE (Design of Experiments).

Outline:
Constructing an Experimental Design

Selecting the Types of Designs
Specifying the Experimental Factors
Specifying the Response Variables
Selecting the Proper Designs
Adding Centerpoints
Blocking and Randomization

Analyzing an Experimental Design

Model Specification
Standardized Pareto Chart
ANOVA Table
Normal and Half-Normal Plots
Excluding Effects
Main Effects Plots
Interaction Plots
Contour and Surface Plots

Augmenting Designs

Adding Additional Fractions
Adding Star Points
Collapsing Designs
Following the Path of Steepest Ascent

Optimization Experiments

Central Composite and Box-Behnken Designs
Finding Optimal Settings of the Experimental Factors


Further Topics in Design of Experiments

This module continues the discussion of using STATGRAPHICS for DOE.

Outline:
Mixture Experiments

Mixture Models
Simplex-Lattice and Simplex-Centroid Designs
Extreme Vertices Designs
Analyzing Mixture Experiments

Multiple Response Optimization

Constructing Desirability Functions
Generating Overlay Plots

D-Optimal Designs

Generating Candidate Runs
Selecting the Optimal Subset
Using D-Optimal Designs to Fix Botched Experiments

Designs with Inner and Outer Arrays

Robust Operating Conditions
Control Variables and Noise Variables
Selecting Orthogonal Arrays
Using Taguchi's Signal-to-Noise Ratios

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