Basic Analysis and Graphing - SAS

46 Performing Univariate Analysis Chapter 2
Options for Continuous Variables
Table 2.8 Description of Options for Continuous Variables (Continued)
Stem and Leaf
CDF Plot
Adds a stem and leaf report, which is a variation of the histogram. See “Stem
and Leaf” on page 49.
Adds a plot of the empirical cumulative distribution function. See “CDF
Plot” on page 49.
Test Mean Performs a one-sample test for the mean. See “Test Mean” on page 50.
Test Std Dev
Confidence Interval
Prediction Interval
Tolerance Interval
Capability Analysis
Performs a one-sample test for the standard deviation. See “Test Std Dev” on
page 51.
Choose confidence intervals for the mean and standard deviation. See
“Confidence Intervals for Continuous Variables” on page 52.
Choose prediction intervals for a single observation, or for the mean and
standard deviation of the next randomly selected sample. See “Prediction
Intervals” on page 53.
Computes an interval to contain at least a specified proportion of the
population. See “Tolerance Intervals” on page 54.
Measures the conformance of a process to given specification limits. See
“Capability Analysis” on page 54.
Continuous Fit Fits distributions to continuous variables. See “Fit Distributions” on page 56.
Discrete Fit Fits distributions to discrete variables. See “Fit Distributions” on page 56.
Save
Saves information about continuous or categorical variables. See “Save
Commands for Continuous Variables” on page 52.
Remove
Permanently removes the variable and all its reports from the Distribution
report.
Normal Quantile Plot
Use the Normal Quantile Plot option to visualize the extent to which the variable is normally distributed. If
a variable is normally distributed, the normal quantile plot approximates a diagonal straight line. This type
of plot is also called a quantile-quantile plot, or Q-Q plot.
The normal quantile plot also shows Lilliefors confidence bounds (Conover 1980) and probability and
normal quantile scales.