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SPSS Training In Nepal

Statistical Package for the Social Sciences (SPSS)

SPSS Statistics is a software package used for interactive, or batched, statistical analysis. Long produced by SPSS Inc., it was acquired by IBM in 2009. The current versions (2015) are named IBM SPSS Statistics. It is also used by market researchers, health researchers, survey companies, government, education researchers, marketing organizations, data miners,and others

SPSS training courses provides full coverage of SPSS statistics from fundamentals to data management, statistical analysis with interpretation of results, statistical methods and techniques for survey analysis.

Course Highlights

SPSS training course is specifically designed to support aspiring surveyors, statisticians and professionals involved in research, data management and data analysis.

Over the years NEITC has conducting a training programme with a special focus on statistical methods only by using a standard statistical sotware such as SPSS. This software is very user friendly and vastly used by academicians/ researchers/ students to analyse the data o research studie/surveys/evaluations etc.

 Benefits of SPSS Training in Super Brain

  1. Personalized feedback on project
  2. Wide access to course materials
  3. Highly qualified and experienced instructors
  4. Motivation and encouragement
  5. Regular interaction with experienced Data analysts involved in working with SPSS in their projects
  6. Comprehensive training methodology
  7. Overall emphasis in practical approach training
  8. Proper instruction and guidance for interpretation of statistical results while performing data analysis.

Syllabus outline:

Please contact us anytime via email, online forms or our Facebook page to secure your seat for upcoming SPSS training session. For further details, please call or visit our office anytime.

Pre-requisites for SPSS Training

  • General Computer literacy

Courses Outline :- SPSS Training in Nepal

  1. SPSS Overview
  2. Defining Variables: Qualitative and Quantitative Variables
  3. Brie Concept of Measurement of scale
  4. Entering Data in the SPSS Spreadsheet
  5. Importing and Exporting Data
  6. Coding the Data
  1. SPSS windows
  2. Define data properties.
  3. Create data entry template using sample questionnaire.
  4. Data entry and cleaning practice.
  5. Handling the different formats of the dataset.
    I. From File
  1. Open new SPSS data & syntax.
  2. Save SPSS data, syntax & output.
  3. Open data of different format & save in different format.
  4. Make data file password protected.
  5. Export pivot tables, charts, logs.
  6. Generate all variable information and all data value labels in table.
  7. II. From Edit
  8. Customize the variable view.
  9. Insert variables/cases in data.
  10. Change the pivot table format.
  11. Find & replace.
  12. Go to exact variable and case number.
  13. Sort ascending descending and multiple variable sorts.
  14. Change the file locations to your folder.
  15. Shown & Hidden log, notes.. in output.
  16. III. From Data
  17. Create duplicate dataset.
  18. Copy data properties for partial/all dataset.
  19. Identify duplicate cases/ identify unusual cases.
  20. Sort variables & transpose data.
  21. Merge two or more files into one.
  22. Define multiple response sets.
  23. Dichotomous
    Categories
  24. Compare dataset for
  25. Change log
    Find accidental modification
  26. Use aggregate/ restructure feature.
  27. Use feature split file
  28. Select cases
  29. Conditional feature selection
    Random cases selection ( approximate/ exact sampling)
    Use of filter variable
    Handle selected cases with same/different/delete features.
    I. From Transform:
  1. Generate random numbers.
  2. Use recode feature
    Automatic recode
    Recode in to same variable
    Recode in to different variable
  3. Use compute variable to compute new variable.
  4. Use of string functions.
  5. Binning for automatic categorization of data.
  6. Date and time wizard
  7. Duration calculation
    Calculate age from DOB.
    Add and subtract days/years/months.
  8. Rank cases
  9. Create time series dataset.
  10. II. From Analyze
  11. Generate codebook of the specific variable.
  12. Find the frequencies of items.
  13. Generate multi- level custom tables.
  14. Generate descriptive statistics from data.
  15. Generate descriptive from supplied variable.
  16. Generate the custom table with title, total, subtotal & not empty values with excluding variable.
  17. Calculate column percentage, row percentage.
  18. Calculate mean, median & minimum values of a scale variable.
  19. III. Statistical Tests:
  20. t-test
  21. One- sample
  22. Independent sample
  23. Paired sample
  24. Correlation (Bivariate)
  25. Regression
  26. Linear regression
    Logistic regression
  27. Reliability analysis.
  28. Chi-square test
    One sample
    Test of independence
  29. Non-parametric test
  1. Generate charts for different types of dataset.
  2. Use chart editor.
  3. Export charts.
  1. Working with syntax.
  2. Window Split for large dataset.

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