Kursen har inget datum. Ring vår kursbokning 077 186 10 37 för information om en privat utbildning.
Översikt
| Kurskod | 0R2A5SE | Leveranstyp | Instructor Led - Online Training
(Hands-on labs) |
|---|---|---|---|
| Kurslängd | 2.0 dagar | Kurstyp | |
| Listpris |
SEK 12 500,00 exkl moms
SEK 15 625,00 inkl moms |
IBM SPSS Education is pleased to offer you our courses in an exciting learning format, Instructor-led Online (ILO). Students are offered a similar experience to live classroom training, with the convenience of having it delivered directly to their desktop.
This course builds on the knowledge acquired during the 'Introduction to Data Management' course and provides more complex functionality within each of the Data Management steps.Students will build on their scripting knowledge and tackle more intricate scenarios.The survey and case data used during this course are the solutions to the IBM SPSS Data Collection Scripting (Survey Creation) Level I course, thereby providing a sense of continuity to students from both classes.Additionally, the solution created during the 'Introduction To Data Management' course will be used to drive the student exercises.
Målgrupp
This course is for scriptwriters who will be responsible for the data management of projects. In order words, taking initial datasets and surveys files and modifying the records appropriately.
Förkunskaper
Students attending this course should have taken
- the 'IBM SPSS Data Collection Scripting (Intro to Data Management)' course as the content builds on specific knowledge gained during that course.
Nyckelområden
- Lesson 1: Course Introduction
- Lesson 2: Survey files and data
- Lesson 3: The Data Management process
- Lesson 4: Options for reading data in and out
- Lesson 5: Adding derived survey variables
- Lesson 6: Actions prior to opening input data
- Lesson 7: Actions after reading Input data
- Lesson 8: Using subroutines and functions
- Lesson 9: Looping through records
- Lesson 10: Error Handling
- Lesson 11: Actions prior to closing output data
- Lesson 12: Actions after data output closed
- Lesson 13: Course Summary