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Statistical Software  Programming Training

  Industries where statistical software can be founded:

- Clinical Research

- Automotive

-Banking

-Financial Services/Insurance

-Government & Education

-Healthcare

-Life Sciences

-Manufacturing

-Media/Entertainment

-Pharmaceutical

-Retail

-Telecommunication

Etc.

This training  program can  help you gain appropriate knowledge and practical skills in order to apply for the position of Statistical Software Programmer.  Upon completion of this  program and after passing on-line final exams you will receive, by mail, a diploma stating your new qualifications.

 

For prices and registration please contact us at info@kriger.com or give us a call

at (866) 757-9791 (USA and Canada) or + 1(416) 630-0038 (Internationally)

To register on-line please click

Register

Please note that all the payments are secure.

 


Statistical Software Programming 
Course Outlines


Session 1 Introduction



Session 2 Briefing
1. The company and the software
2. Statistical software V8 On Windows environment
3. Simple programs





Session 3 Basic concepts
Sessions, steps, temporary/permanent dataset, dataset name, observations,
variables, naming conventions, char, numeric, date, ending comments,
documentations, options for sessions/steps/statements etc.





Session 4 Data Input
1. Input methods: list, column, formatted, named, and mixed, default
delimiter
2. Column pointer, line pointer, repeated read, implicit data step loop





Session 5 Data Input
1. Length, informat statements
2. External files, filename, infile





Session 6 More Data Input
1. Input modifiers, infile options
2. Do loop input, output





Session 7 More Data Input
1. Proc import
2. Import wizard





Session 8 Simple Output
1. Proc print, sort, contents, format
2. Proc mean, summary, unvariate, freq
3. Proc report





Session 9 Language elements
1. Operators, expressions
2. Functions for date, numeric, char





Session 10 Language elements
1. More functions
2. Conditional statements if, where, select





Session 11 Objectives:
1. Sort, First./Last., and retain
2. Array and loop
3. Variable regrouping





Session 12 Objectives: Dataset combination
1. Stacking with set, append
2. Interleaving with set by





Session 13 Dataset combination
1. Merge
2. Update master set with transaction





Session 14 Data cleaning
1. Identify dirty data with proc freq
2. Identify dirty data with proc mean (min, max), proc univarite (extreme
values)
3. Identify dirty char data with char functions





Session 15 Dataset transformation
1. By proc transform
2. By array





Session 16 Longitudinal data samples
1. With lag, dif
2. With First./ and retain
3. With multiple set statement





Session 17 Combining summary with individual observations





Session 18 Introductory to Proc SQL
1. Create table
2. Insert
3. Update
4. Select





Session 19 Introductory to Proc SQL
1. More select
2. Dataset combination with SQL vs. with data step





Session 20 Macro by sample
1. Macro variable
2. Macros programming
3. Macro functions





Session 21 More Macro 




Session 22 Summary report Proc tabulate 




Session 23 Summary report
Proc report





Session 24 ODS
Sample of ODS





Session 25 Efficiency
1. SAS data step compilation and execution
2. Efficient programming





Session 26 Common program errors





Session 27 Samples of statistics procedures
1. Ttest
2. Anova





Session 28 Samples of statistics procedures
1. Corr
2. Reg





Session 29 Samples of Drawings
1. Plot
2. Chart





Session 30 Data security in SAS
1. Password
2. Lock
3. Encryption





Session 31 Data security in SAS Continued
1. Integrity constrains
2. Audit trail
3. E-mail automation

FINAL EXAM

For prices and registration please contact us at info@kriger.com or give us a call

at (866) 757-9791 (USA and Canada) or + 1(416) 630-0038 (Internationally)

To register on-line please click

Register

Please note that all the payments are secure.