Duration: 1 month


SPSS Training in Nepal, is that what you are looking for? If yes, you have landed on the right page. IT Training Nepal conducts SPSS Course and Certification taught by industry experts.

SPSS is a windows based statistical analysis tool obtained by IBM. Social science scholars, as well as business researchers, feel the value of SPSS through the research and invention. The first version of SPSS was released in 1968 by Norman H. Nie and C. SPSS is used as a research weapon in different sectors. SPSS is popular in the sector of social science, health, marketing, medical, research centers and many more. We learn how to use the SPSS software and how to analyze the data to prepare the scientific report. Data management and data documentation are the key features of SPSS software.

You will learn how to use the software along with that you will also learn how to analyze data and generate different reports.


Introduction to data is the beginning of the SPSS course. We learn about different forms of raw data such as notepad, MS Excel, MS Access, Strata and many more and how to feed those data to SPSS software. This course starts with basic data analysis to advance Univariate analysis and data transformation. Statistical, as well as graphical analysis, goes further in this course and we take the sampling practice to learn better.

Then slowly and gradually the course will move towards advanced topics of data analysis like the chi-squared test, T-test, one-way ANOVA, two-way ANOVA, linear regression, correlation, multiple regression, Factor analysis and so on. After completion of this course, the individual will be able to handle any analytical research work easily and quickly. The scope of SPSS will be always there for scholars and researchers.


After successful completion of SPSS course training, students shall be able to do the following task:

  • SPSS as a data analysis tool
  • Creates own analytic features
  • Feeds information (samples)
  • How to enter and arrange information within SPSS software
  • How to summarize research findings with the help of appropriate indexes and tables
  • To interpret results graphically using different charts
  • The basic principles of inferential statistics
  • To perform inferential statistical analysis
  • To integrate information and build models out of it
  • To edit SPSS output and use it to produce fine research reports


Any individual who is interested in SPSS software can join the training. Mostly, students of Masters, PhD, and people working in I/NGOs are interested to join the course. Data analysts are highly encouraged to apply for the course.


Lesson 1: Introduction of SPSS, Data types, Measurement and Scale

Lesson 2: Introduction of SPSS for window

Lesson 3: Reading Raw data File: from excel, notepad, R, Stata and databases

Lesson 4: Univariate analysis

  1. Basic descriptive statistics. Measures of central tendency: mean, Median, mode. Measures of dispersion: range, standard deviation, variance.
  2. Frequencies and Distribution
  3. Other basic Univariate procedures: Explore, Crosstab

Lesson 5: Transforming the data and Conditional Computes : the IF command

  1. Computing new variables
  2. Redefining or reorganization of existing data.
  3. Filtering the data
  4. Weighing Cases
  5. Sorting
  6. Replacing the missing values
  7. Using subsets of variables

Lesson 6: Selecting and Sampling Cases

Lesson 7: Numerical and Graphical Summaries of data Histogram, Box-plots, Bar-chart, Scatter Plots, stem and Leaf etc

Lesson 8: The Chi-Squared Test Observed and Expected Frequencies, Degree of freedom, Chi-Squared distribution

Lesson 9: Two-Sampled and Paired Samples T-Test, One-way and Two –way ANOVA (Comparing Multiple Independent Means)

Lesson 10: Simple Linear Regression, Types of relationship, Scatter Plots and Lines of Best Fit

Lesson 11: Correlation and Multiple Regression Strength of Linear Relationship, Multiple Linear Regression, Enter/Step Wise method

Lesson 12: Logistic regression Assumptions, Details of example, Data Preparation, Coding of responses, Strength of relationship, Binary Logistic and Multi-nominal Logistic

Lesson 13: Factor Analysis Assumptions, Factors involved in factor analysis, Procedures of factor analysis

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