The User Manager in SAS Management Console provides three default roles
for the SAS Add-In for Microsoft Office: Advanced, OLAP, and Analysis. The
following table describes the capabilities that are assigned by default to
these roles.
Default Capabilities Assigned to Roles for the SAS Add-In for Microsoft Office
|
|
|
Role |
|
Capability |
Description |
Advanced |
OLAP |
Analysis |
|
Open or Import Category |
|
|
|
|
|
Open Files from Local Computer |
Open files from the local file system. Not a substitute for system security. |
X |
X |
X |
|
Open Cube from OLAP Servers |
Open cube source data into a document. |
X |
X |
|
|
Save or Distribute Category |
|
|
|
|
|
Modify Output Data Location in SAS Tasks |
Change the output location in tasks that have an output location. |
X |
|
X |
|
Copy and Paste SAS Server Content |
Copy or paste from a server or library. Not a substitute for system
security. |
X |
|
X |
|
Publish To Distribution Channels |
Send content to a channel such as e-mail or Web, modify channel properties. |
X |
|
|
|
Content Category |
|
|
|
|
|
Add or Modify Custom Code to SAS Tasks |
Edit custom code runs before or after SAS tasks. |
X |
|
|
|
Options Category |
|
|
|
|
|
Modify SAS Server Reference in Project or Document |
Enable server reassignment in SAS content. |
X |
|
X |
|
Modify Security Options |
Change security options for documents. |
X |
|
|
|
Modify E-mail Options |
Change e-mail options for documents. |
X |
|
|
|
Modify All Options |
Change all options in the SAS Add-In Options window. |
X |
|
|
|
Tools and Help Category |
|
|
|
|
|
Access Unregistered Custom Tasks |
Edit or run unregistered tasks if security enables access. |
X |
|
|
|
Modify Styles |
Change ODS output styles. |
X |
|
|
|
Create or Modify Schedules |
Change document refresh schedules or scheduling options. |
X |
|
X |
|
Access SAS Technical Support |
Use the Help menu to navigate to SAS technical support. |
X |
|
|
|
Data Category |
|
|
|
|
|
Copy to SAS Server |
Copy active data to a SAS server. |
X |
X |
X |
|
Compare Data |
Create a report that compares two data sets or two variables across
multiple data sets. |
X |
X |
X |
|
Data Set Attributes |
Create a report with the data set's creation date, location, number
of observations, variable names, labels, types, and formats. |
X |
X |
X |
|
Random Sample |
Create an output data set that contains a random sample of the rows
in the input data set. |
X |
X |
X |
|
Rank |
Compute ranks for numeric variables across the observations of a SAS
data set and send the ranks as output to a new SAS data set. |
X |
X |
X |
|
Sort Data |
Sort a data source by any of its columns. |
X |
X |
X |
|
Standardize Data |
Create an output data set by standardizing the variables in a data source
to a given mean and standard deviation. |
X |
X |
X |
|
Split Columns |
Create an output data set by splitting the unique combination of values
of the selected columns in the input data set into multiple columns. |
X |
X |
X |
|
Stack Columns |
Create an output data set by restructuring selected columns in the input
data set so that these columns are transposed into observations. |
X |
X |
X |
|
Transpose a Set of Data |
Turn the selected columns of a data source into the rows of an output
data set. |
X |
X |
X |
|
Describe Category |
|
|
|
|
|
List Report Wizard |
Create detail or summary reports. |
X |
X |
X |
|
Distribution Analysis |
Create a data summary with distribution information for numeric variables.
Used to create plots. |
X |
X |
X |
|
Characterize Data |
Create a summary report with graphs of frequency and univariate statistics
for SAS data sets. |
X |
X |
X |
|
List Data |
Print the observations in a SAS data set, using all or some of the variables,
from a variety of reports. |
X |
X |
X |
|
One-Way Frequencies |
Generate frequency tables or perform binomial and chi-square tests. |
X |
X |
X |
|
Summary Statistics |
Compute descriptive statistics for variables across all or groups of
observations, or summarize data in a graphical display. |
X |
X |
X |
|
Summary Tables |
Display descriptive statistics for selected variables in a variety of
tables. |
X |
X |
X |
|
Table Analysis |
Generate crosstabulation tables, also known as contingency tables. |
X |
X |
X |
|
Graph Category |
|
|
|
|
|
Contour Plot |
Create line, filled, pattern, or smooth plots that show the mathematical
relationships between three numeric variables. |
X |
X |
X |
|
Bubble Plot |
Create a bubble plot that displays up to five dimensions (X, Y, size,
color, and time). |
X |
X |
X |
|
Radar Chart |
Create radar or star charts that show the relative frequency of data
measures. |
X |
X |
X |
|
Box Plot |
Create box plots, hi-lo charts, or hi-lo-close charts that display multiple
summary statistics for a numeric variable across the values of a chart variable. |
X |
X |
X |
|
Donut Chart |
Create simple or group charts that show the relative contribution of
the parts to the whole. |
X |
X |
X |
|
Area Plot |
Create area, spline, step, or overlay plots. |
X |
X |
X |
|
Pie Chart |
Create simple or group charts that show the relative contribution of
the parts to the whole. |
X |
X |
X |
|
Line Plot |
Create line, scatter, spline, needle, step, regression, smooth, STD,
Lagrange interpolation, or overlay plots. |
X |
X |
X |
|
Bar Chart |
Create vertical, horizontal, or three-dimensional bar charts. |
X |
X |
X |
|
Create Map Feature Table |
Create a feature table for map data sets and convert spherical coordinates
to Cartesian coordinates. |
X |
X |
X |
|
Surface Plot |
Create three-dimensional wireframe plots, smooth plots, or gradient
plots. |
X |
X |
X |
|
Map Graph |
Create a two-dimensional (choropleth) or three-dimensional (block and
prism) color map that shows the variation in the value of a response variable
for different geographical areas. |
X |
X |
X |
|
Bar-Line Chart |
Create a vertical bar chart with a line plot overlay. The line plot
represents the value of a statistic that is calculated for a variable. |
X |
X |
X |
|
Scatter Plot |
Create two-dimensional scatter plots, three-dimensional scatter plots,
or three-dimensional needle plots. |
X |
X |
X |
|
ANOVA Category |
|
|
|
|
|
Linear Models |
Analyze data using the least squares to fit general linear models. |
X |
X |
X |
|
Mixed Models |
Fit a variety of mixed linear models to data and use these fitted models
to make statistical inferences about the data. |
X |
X |
X |
|
Nonparametric One-Way ANOVA |
Run nonparametric tests for location. The task also scales differences
across a one-way classification and provides a standard analysis of variance
on the raw data. |
X |
X |
X |
|
One-Way ANOVA |
Test for differences among the means of the levels and quantify these
differences. |
X |
X |
X |
|
t Test |
Perform t-tests for one sample, two samples, and paired observations. |
X |
X |
X |
|
Regression Category |
|
|
|
|
|
Generalized Linear Models |
Model data that is not normally distributed. Also model data for which
the mean has been restricted to a range of values. Also model data for which
the variance is not constant. |
X |
X |
X |
|
Linear Regression |
Perform linear regression analysis on multiple dependent and independent
variables. |
X |
X |
X |
|
Logistic Regression |
Investigate the relationship between discrete responses and a set of
explanatory variables. |
X |
X |
X |
|
Nonlinear Regression |
Produce least squares or weighted least squares estimates of the parameters
of a nonlinear model. |
X |
X |
X |
|
Multivariate Category |
|
|
|
|
|
Canonical Correlation |
Examine the relationship between linear combinations of X and Y variables. |
X |
X |
X |
|
Cluster Analysis |
Create hierarchical clusters of coordinate data or distance data. |
X |
X |
X |
|
Correlations |
Determine the relationship between numeric variables by calculating
correlation coefficients. |
X |
X |
X |
|
Discriminant Analysis |
Develop a discriminant criterion that can be used to classify variables
into the groups defined by the classification variable. |
X |
X |
X |
|
Factor Analysis |
Perform a variety of common factor and component analyses and rotations. |
X |
X |
X |
|
Principal Components |
Examine relationships among several variables. This task can be used
for summarizing data and detecting linear relationships. |
X |
X |
X |
|
Survival Analysis Category |
|
|
|
|
|
Life Tables |
Compute nonparametric estimates of the survival distribution of data
that may be right-censored due either to withdrawals or to termination of
the study. |
X |
X |
X |
|
Proportional Hazards |
Perform regression analysis of survival data based on the Cox proportional
hazards model. |
X |
X |
X |
|
Capability Category |
|
|
|
|
|
CDF Plots |
Plot the observed cumulative distribution function (CDF) of a variable. |
X |
|
|
|
Histograms |
Compare the distribution of measurements from a process in statistical
control to its specification limits. |
X |
|
|
|
Q-Q Plots |
Compare ordered values of a variable to the quantiles of a specified
theoretical distribution, such as the normal distribution. |
X |
|
|
|
Probability Plots |
Compare ordered values of a variable to the percentiles of a specified
theoretical distribution, such as the normal distribution. |
X |
|
|
|
P-P Plots |
Compare the empirical cumulative distribution function (ECDF) of a variable
to a specified theoretical cumulative distribution function, such as the normal
distribution. |
X |
|
|
|
Control Charts Category |
|
|
|
|
|
Box Chart |
Create a mean chart for the subgroup means. The task superimposes the
box-and-whisker plots of the measurements for each subgroup onto the mean
chart. |
X |
X |
X |
|
c Chart |
Create c charts for the numbers of nonconformities (defects) in the
subgroup samples. |
X |
X |
X |
|
Individual Measurements Chart |
Create control charts for the individual measurements and the moving
ranges. |
X |
X |
X |
|
np Chart |
Create np charts for the numbers of nonconformities (defects) in the
subgroup samples. |
X |
X |
X |
|
p Chart |
Create p charts for the proportions of nonconforming (defective) items
in the subgroup samples. |
X |
X |
X |
|
u Chart |
Create u charts for the numbers of nonconformities (defects) per inspection
unit in the subgroup samples that contain arbitrary numbers of units. |
X |
X |
X |
|
Mean and Range Chart |
Create mean and range charts for the subgroup means and the subgroup
ranges. |
X |
X |
X |
|
Mean and Standard Deviation Chart |
Create mean and standard deviation charts for the subgroup means and
the subgroup standard deviations. |
X |
X |
X |
|
Pareto Category |
|
|
|
|
|
Pareto Chart |
Create a chart that displays the relative frequency of problems in a
process as bars. Pareto charts help the user identify the problems that deserve
the most attention. |
X |
|
|
|
Time Series Category |
|
|
|
|
|
Forecast Studio Create Project |
Specify the forecasting variables, choose whether to forecast your data
hierarchically, and specify the forecast horizon for a new SAS Forecast Studio
project. |
X |
X |
X |
|
Forecast Studio Open Project |
Open the selected series from an existing SAS Forecast Studio project
and specify how to display the results. |
X |
X |
X |
|
Forecast Studio Override Project |
Submit overrides for the forecast data in an existing SAS Forecast Studio
project. |
X |
X |
X |
|
ARIMA Modeling and Forecasting |
Analyze and forecast equally spaced univariate time series data, transfer
function data, and intervention data by using the ARIMA or ARMA model. |
X |
X |
X |
|
Regression Analysis with Autoregressive Errors |
Estimate and forecast linear regression models for time series data
when the errors are not independent through time or the error variance is
not constant. |
X |
X |
X |
|
Basic Forecasting |
Generate forecasts for many time series in one step. This task uses
extrapolative forecasting methods where the forecasts for a series are functions
only of time and past values. |
X |
X |
X |
|
Regression Analysis of Panel Data |
Analyze panel data sets that consist of time series observations on
each of several cross-sectional units. The task uses a class of linear econometric
models to analyze the data. |
X |
X |
X |
|
Prepare Time Series Data |
Prepare data for analysis by time series tasks or other tasks. |
X |
X |
X |
|
Create Time Series Data |
Convert transactional data into fixed-interval time series. Transactional
data is time-stamped data that is collected over time with irregular or varied
frequency. |
X |
X |
X |
|
Model Scoring Category |
|
|
|
|
|
Model Scoring |
Score a data set against an existing SAS Enterprise Miner predictive
model. |
X |
X |
X |
|
SAS Management Console 9.2 Category |
|
|
|
|
|
Access Unregistered Plug-ins |
Access plug-ins that are not registered in metadata. |
X |
|
|
