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Introduction to IBM SPSS

SPSS is widely covered due to its straightforward and English-like command language and impressively thorough user manual. SPSS is considered and accepted as an extremely powerful tool for manipulating and deciphering survey data. 

SPSS is used by market researchers, health researchers, survey companies, government entities, education researchers, marketing organisations, data miners, and many more for processing and analysing survey data.

 Major Benefits:

  •  SPSS offers reliable and fast answers.
  • It has very dynamic and useful tables and graphs
  • Better user interface compared to other software.
  • Provides feedback in decision making.
  • Various types of complex statistical tests are available as a built-in feature.
  • Higher Job opportunities.

Popular Career Opportunities:

  • Data Analyst
  • Thesis Analysis
  • Research Analyst
  • Data scientist


The course is designed to provide students with transferable skills, to understand the uses of SPSS, as a tool to summarise and aid in the interpretation of research findings.

On completing this course students will:

  • Be comfortable using SPSS as a data analysis tool.
  • Understand how to work with SPSS.
  • Learn to use new features of SPSS on their own.
  • Acquire information (samples).
  • Enter and reorganise information within SPSS.
  • Effectively summarise research finds using SPSS through the use of appropriate indexes and tables.
  • Able to choose charts to successfully highlight their research results.
  • Able to understand and interpret charts.
  • Understand the basic principles behind inferential statistics.
  • Carry out inferential statistical analysis using SPSS.
  • Integrate information and build models.
  • Edit SPSS output.
  • Use SPSS output to produce scientifically sound research reports.


Course Content

  • Introduction to SPSS
  • Overview of SPSS for Windows
  • Navigating
  • Getting your data in
  • Import Data from Excel, CSV File
  • Importing Data from a Text File
  • Saving your work
  • The Data Editor
  • The Syntax Editor
  • The Output Viewer
  • Creating and Defining Variables
  • Inserting and Deleting Cases and Variables
  • Computing New Variables
  • Using Condition during computing variable
  • Recoding Variables
  • Sorting Cases
  • Selecting Cases
  • What is Syntax?
  • Basic Syntax Rules
  • Using Syntax
  • Comparing Drop-Down Menus versus Syntax
  • When should I use syntax?
  • Learning Syntax
  • Mean, Sum, Standard Deviation, Variance
  • Minimum Value, Maximum Value, and Range
  • Frequency distributions
  • Bar Diagram
  • Line Diagram
  • Scatter Plot
  • Leaf and Stem Diagram
  • Box Plot
  • Table Builder Interface
  • Stacking Variables
  • Nesting Variables
  • Layers
  • Stacking Categorical Variables
  • Stacking with Crosstabulation
  • Nesting Categorical Variables
  • Swapping Rows and Columns
  • Pearson Correlation
  • Common Uses
  • Data Requirements
  • Hypotheses
  • Test Statistic
  • Data Set-Up
  • Run a Bivariate Pearson Correlation
  • Example: Understanding the linear association between weight and height
  • Example: Predicting Job Performance from IQ
  • Scatterplot Performance with IQ
  • Pearson Correlation Performance with IQ
  • Linear Relation – General Formula
  • Prediction Formula for Performance
  • B Coefficient – Regression Slope
  • Regression Intercept (“Constant”)
  • Chi-Square Test
  • Application of Chi Square distribution
  • Data Requirements
  • Hypotheses
  • Test Statistic
  • Data Set-Up
  • Run a Chi-Square Test of Independence
  • Example: Chi-square Test for 3×2 Table
  • Example: Chi-square Test for 2×2 Table
  • One Sample t Test
  • Common Uses
  • Data Requirements
  • Hypotheses
  • Test Statistic
  • Data Set-Up
  • Run a One Sample t Test
  • Example
  • Paired Samples t Test
  • Common Uses
  • Data Requirements
  • Hypotheses
  • Test Statistic
  • Data Set-Up
  • Run a One Sample t Test
  • Example
  • Independent Samples t Test
  • Common Uses
  • Data Requirements
  • Hypotheses
  • Levene’s Test for Equality of Variances
  • Test Statistic
  • Data Set-Up
  • Run an Independent Samples t Test
  • Example: Independent samples T test when variances are not equal
  • One-Way ANOVA
  • Common Uses
  • Data Requirements
  • Hypotheses
  • Test Statistic
  • Data Set-Up
  • Run a One-Way ANOVA
  • Example

About the instructor


BI Solution Architect

Hi I am Dipu Maharjan. I am working as BI Solution Architect. I have experience more than 13 years as Data Analyst, Database Programmer, BI Developer and Trainer.
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Roji Maharjan

I met my expectations; Before I joined the class I used to get afraid of seeing numbers as well as stats problems. Today I learned about being more confident working with numbers. Facilitation was very simple and easy to grab.

Everything was completed very smoothly.

Thank you!

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Raju Bhole

Excellent Management and Learing Environment to learn, discuss on SPSS relateing to research work

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Bijaya Man Shrestha

The way of teaching was very good and easy to learn from our respected teacher.

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Deepak Thapa

  • Very helpful/Fruitful contents
  • Tutor very energetic good way
  • Course TIme is a little short for me

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Sabina Bhattrai

It had been a good experience, SPSS training helped me gain proficiency in data analysis and statistical modeling. I learned how to import, clean, and analyze data using various techniques. The training enhanced my ability to derive meaningful insights and make informed decisions based on statistical results. Please inform me if there are any other such courses.

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    Course Features

  • Total Credit Hours30 hrs
  • Course CostUSD 119.52