Control Chart Analysis/Analysis of Means
Control Chart Analysis uses the industry-proven effective Western Electric Rules for detecting shifts on X-MR Control Charts. Shifts can be detected away from the process average or target as well as from the previous shift. This shift-away feature is unique to CCA©. In addition to the X-chart analysis CCA/ANOM© will simultaneously perform a Moving Range Chart Analysis to determine if process control is improving or getting worse.
Non-normally distributed data are often encountered in the real world and CCA/ANOM© can handle those as easily as other packages handle normal data. CCA/ANOM© provides data transformations for normalizing data and can automatically generate asymmetric control limits for skewed distributions.
Probability plots are an important tool in determining whether or not a distribution is normal and CCA/ANOM© completely automates this tool. Other tests for finding unusual patterns in the data, such as runs and trends, are quickly and efficiently accomplished.
Process indices show how well a process is performing relative to specifications or how well it could perform. Using CCA/ANOM©, you can quickly calculate the Process Performance Index and Process Capability Index for both normal and non-normal distributions.
C-charts are available for use in situations where processes are sampled and count data are being studied.
Designed for non-statisticians, CCA/ANOM© makes the powerful tool of control charting easy to use for anyone. The Windows® format means that you do not need to learn any special commands or format specifications. Results are presented in clear and concise terms with a minimum of statistical terminology.
Features of Control Chart Analysis/Analysis of Means
Operating System Requirements
Windows 95®, Windows 98®, or Windows NT®
Tab delimited files or cells copied and pasted from a spreadsheet format
Can accept a missing data code
Can transform data without altering the data file
Mean, median, maximum, minimum, standard deviation
Moving Range Statistics
Average moving range, Spcl
Starting Point Options
Choice of Starting Point includes Average, Median, Zero, First Point or a Custom Value
Shows both upper and lower control limits
Allows user to specify process target and process control standard deviation
Process Performance Index (PPI), Process Capability Index (PCI)
For normal or non-normal data
One or two process specs
Partitioning of Variation
Separates variation into long-term, short-term and test variation
Determines if Stotal and Spcl are significantly different
Runs and Skew Analysis
Length of Runs
Number of Runs
Trends (Runs Up and Down)
Initial Data Plots about Median or Average
Normal Probability Plots
Control Chart Analysis
X-MR Charts for Normal and Non-normal distributions
Uses the industry-proven Western Electric Rules for detecting shifts
Identifies shifts away from the process average or target
Determines when process average shifts from the previous process average
User can override control limits
Analysis of Means
Analyzes any number of groups greater than or equal to two
Analyzes equal or unequal numbers of observations per group
Calculates standard deviation for time ordered and non-time ordered data
Calculates the Halperin test statistic for 10 percent level of significance
Summarizes decision limits and averages in a graphical display
Harold S Haller & Company
31004 Nantucket Row, Cleveland, OH 44140-1050
Phone: (440) 871-6597; Fax: (440) 871-1889