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Comparación de versiones

Comparación de versiones de SYSTAT

= Available
= Not available
* = Add-on module feature
Statistics Systat Version
13.2
12.0
11.0
10.2
Trimmed Mean – Row & Column
Standard Error
Confidence Interval
Windsorized Mean – Row & Column
Standard Error
Confidence Interval
Probability calculator
Mode – Row
Interquartile Range
Random sampling
Univariate discrete and continuous distributions
Multivariate distributions *
Design of experiments
Power analysis
Descriptive Statistics
Column
Row
N-tiles, P-tiles
Fitting distributions
Crosstabulation and measures of association
List layouts, list first n levels, display rows with zero counts
Mode for one-way tables
Correspondence analysis
Simple
Multiple
Loglinear models
Nonparametric tests
Jonckheere-Terpstra
Fligner-Wolfe
Dwass-Steel-Critchlow-Fligner and Conover-Inman
Kruskal-Wallis
Two-sample Kolmogorov-Smirnov
Sign
Wilcoxon signed rank
Friedman
Quade
One-sample Kolmogorov-Smirnov
Anderson-Darling
Wald-Wolfowitz runs
Multinormal tests
Hypothesis Testing
Mean
Variance
Correlation
Proportion
Bootstrap-based p-values for all tests for mean and variance
One and two sample Hotelling T2 test for mean vector of multivariate data
Correlations, distances and similarities
Set and canonical correlations
Cronbachs alpha
Linear regression
Save standard errors, confidence intervals
Least squares
Bayesian
Ridge
Best subsets
Find the best models given the number of predictors Best model by R2, Adjusted R2, Mallow’s Cp, MSE, AIC, AICc and BIC
Polynomial
Single independent variable up to order 8, Natural and orthogonal methods Goodness-of fit-statistics (R2 and adjusted R2) and ANOVA with p-values for all models down to linear Quick Graphs: Confidence and prediction interval plots along with estimates, and a plot of residuals versus predicted values
Robust regression
Least Absolute Deviation (LAD)
M
Least Median of Squares (LMS)
Least Trimmed Squares (LTS)
Scale (S)
Rank
Logistic regression
Binary, multinomial, discrete choice and conditional through separate simplified interfaces and input data formats
Specify the reference level for binary and multinomial response models
Probit analysis
Partial least squares regression
Two stage least squares regression
Mixed Regression
Smooth and plot
Nonlinear regression
ANOVA
Options to test normality and homoscedasticity assumptions, including Levene’s test based on median
MANOVA
General Linear Model
Mixed model analysis
Discriminant analysis
Classical Discriminant Analysis (Linear or quadratic)
Robust Discriminant Analysis (Linear or quadratic)
Cluster analysis
Hierarchical
K-means
Additive trees
Factor analysis
Confirmatory Factor Analysis
Maximum likelihood, Generalized Least-Squares, and Weighted Least-Squares methods of estimation of parameters of the CFA model
Goodness-of-Fit Index (GIF), Root Mean Square Residual (RMR), Parsimonious Goodness-of- Fit Index (PGFI), AIC, BIC, McDonald’s Measure of Certainty, and Non-Normal Fit Index (NNFI) to measure the degree of conformity of the postulated factor model to the data
Time series
ARCH models: BHHH, BFGS, and Newton-Raphson implementations, forecasts for error variances using the parameter estimates, Jarque-Bera test for normality of errors, McLeod and Lagrange Multiplier tests for ARCH effect
GARCH models: BHHH, BFGS, and Newton-Raphson implementations, forecasts for error variances using the parameter estimates, Jarque-Bera test for normality of errors, McLeod and Lagrange Multiplier tests for ARCH effect
Time series plot
ACF, PACF, CCF
Transform
Moving average, LOWESS, exponential, smoothing
Seasonal adjustment
ARIMA
Trend analysis
Fourier transformation
Missing value analysis
Quality analysis
Histogram
Pareto chart
Box-and-Whisker Plot
Process capability analysis
Control charts
Survival analysis
Response surface methods
Path analysis (RAMONA)
Conjoint analysis
Multidimensional scaling
Perceptual mapping
Partially Ordered Scalogram Analysis with Coordinates (POSAC)
Test item analysis
Signal detection analysis
Spatial statistics
Classification and regression trees
Monte Carlo (Add-on)
IID Monte Carlo *
Rejection sampling *
Adaptive Rejection Sampling (ARS) *
Markov Chain Monte Carlo (MCMC) algorithms *
Metropolis-Hastings (M-H) algorithm *
Gibbs sampling algorithm *
Monte Carlo integration *
Quality analysis (Add-on)
Gauge R & R studies *
Sigma measurements *
Taguchi’s on-line SPC *
Signal-to-Noise ratio analysis of Taguchi loss functions *
Environment Variables – Column
General Options Systat Version
13.2 12.0 11.0 10.2
Customizable toolbars
Auto-hide Workspace and Commandspace
Store and retrieve current settings for several options including active data file, value label display format, and variable label display format
Tabbed dialog boxes with tabs arranged vertically
Import Business Objects
Save view-mode data files
Close data files that are no longer needed in a given session
Drag-and-drop data from editors that support dragging of content, including the Commandspace, into the Data Editor
Define and call macros in your command scripts
Open legacy command files for direct execution in the current version
Specify the field width, number of decimal places, locale and digit grouping for numeric output
Specify colors in terms of their RGB component values
45 built-in colors
Overlaid graphs, pie charts, and stacked bar charts colored in such a way as to provide more contrast between adjacent elements
Windows XP-style grids in the Data/Variable Editor and dialog boxes
Advanced customizable Status Bar with items to toggle global settings, data processing conditions, and states of the Insert, Caps Lock, Num Lock and Scroll Lock keys on the keyboard
Token dialog boxes to make choices that are mapped to underlying command files
Data Edit Bar
View toolbars using the View menu
Default variable format, distinct from numeric output format, for newly created variables in the Data Editor
Global option to trim leading and trailing spaces in string variable data
Database capture
Startpage
Variable Editor
View Value Labels and data values in data editor
View Variable Statistics and Histogram in data editor for a variable
Windows Menu
Quick Access Menu
Examples tab in Workspace and Customizing Examples
Customizable Interface themes
Apply theme
Save theme
Download theme
Customization of resources
File Comments in Data Editor
Interlinked Command Line and and Dialog Interface
Case selection Tools
Crash Recovery and Rescue System
Windows XP Style Interface
Autocomplete Commands
Opening multiple command files
Command Coloring
Opening Multiple Data Files (View and Active Modes)
Create a new data file by double-clicking in the empty area in Viewspace
Opening Multiple Graphs (View and Active Modes)
Saving Command Files in the ANSI Format
Active Tab at the Beginning of Viewspace/Commandspace
Collapsible links for each section of the output
Output, data and graph editor in a single tabbed window
Global output scheme options
Detailed output organizer node captions
Advanced customizable status bar
New popup menu creation in the Menu Bar
Import data formats
SigmaPlot
Statview
Stata
Statistica
JMP
Minitab
S-Plus
ASCII
Microsoft Excel
SAS
SPSS
BMDP
dBASE
Arc View
Dif
Lotus
Symphony
MDB
Export data formats
Stata
Statistica
JMP
Minitab
S-Plus
ASCII
Microsoft Excel
SAS
SPSS
BMDP
dBASE
Arc View
Dif
Lotus
Symphony
Matrix computations
Random number generator
Mersenne-Twister algorithm
Wichman-Hill algorithm
Save output as RTF or HTML
Save output as MHT
Online HTML Help with Context Sensitive Help
Systat Manuals
Getting Started
Statistics I
Statistics II
Statistics III
Graphics
Data
Language Reference
Knowledge base (FAQ)
Bubble Help
Customizable Main Menus and Right Mouse Button Menus
Sub dialog boxes under different tabs of a main dialog box
Icons to indicate Category,Frequency and Weight variables in dialog boxes
Grid controls with keyboard shortcuts for navigation in Dialog boxes
Variable labels as tooltip on mouse hover in dialog boxes
Whats this’ help for each item in the dialog box
Saving output graph formats
BMP
EPS
EMF
JPG
PICT
WMF
CGM
GIF
TIFF
PS
PNG
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