SPSS Statistics Foundation Course: From Scratch to Advanced

A complete step by step course to master IBM SPSS Statistics for doing advanced Research & Data Analysis
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  • Lectures 73
  • Length 5.5 hours
  • Skill Level All Levels
  • Languages English
  • Includes Lifetime access
    30 day money back guarantee!
    Available on iOS and Android
    Certificate of Completion
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About This Course

Published 7/2016 English

Course Description

Data is the new frontier of 21st century. According to a Harvard Business Report (2012) data science is going to be the hottest job of 21st century and data analysts have a very bright career ahead. This course aims to equip learners with ability of independently carrying out in-depth data analysis with professional confidence and accuracy. It will specifically help those looking to derive business insights, understand consumer behaviour, develop objective plans for new ventures, brand study, or write a scholarly articles in high impact journals and develop high quality thesis/project work.

A good knowledge of quantitative data analysis is a sine qua none for progress in academic and corporate world. Keeping this in mind this course has been designed in such way that students, researchers, teachers and corporate professionals who want to equip themselves with sound skills of data analysis and wish to progress with this skill can learn it in in-depth and interesting manner using IBM SPSS Statistics.

Lesson Outcomes

On completion of this course you will develop an ability to independently analyze and treat data, plan and carry out new research work based on your research interest. The course encompasses most of the major type of research techniques employed in academic and professional research in most comprehensive, in-depth and stepwise manner.


The focus of current training program will be to help participants learn statistical skills through exploring SPSS and its different options. The focus will be to develop practical skills of analyzing data, developing an independent capacity to accurately decide what statistical tests will be appropriate with a particular kind of research objective. The program will also cover how to write the obtained output from SPSS in APA format.


A love for data analysis and statistics, research aptitude and motivation to do great research work.

What are the requirements?

  • The course is built from scratch so no prior knowledge of SPSS or Statistics is required. We cover all the required details in the course both theory and practical part.
  • The learners must have a copy of SPSS software to practise the steps taught in this course.

What am I going to get from this course?

  • Analyse any type of numerical data using SPSS with confidence
  • Independently plan your research study from scratch.
  • Understand the research design and results presented in high quality journal articles
  • Do data analysis accurately and present the results in standard format.

Who is the target audience?

  • PhD students and researchers looking to master SPSS skills and publish in high impact journals
  • Professionals looking for a career in analytics in corporate sector
  • Faculty members looking to master SPSS and advance their data analysis skills

What you get with this course?

Not for you? No problem.
30 day money back guarantee.

Forever yours.
Lifetime access.

Learn on the go.
Desktop, iOS and Android.

Get rewarded.
Certificate of completion.


Section 1: Introduction

This lecture tells you about instructor expertise and his SPSS bio and how he can make a significant difference to your research life. 

Section 2: Downloading and Installing SPSS

This video lecture guides students in a step wise manner about downloading IBM SPSS Statistics 24 and installing it on a Windows laptop/computer. 

Downloading SPSS Grad Pack: Student Version
Section 3: Conceptual Foundation of Statistics
Statistics: Definition and Types
Parametric vs Non-Parametric Statistics: Assumptions
Section 4: Data Entry: Learning to Enter Data in SPSS
Conceptualizing Variables: IV, DV, Control, Moderators & Mediating Variables
Variable Type Numeric: Defining Names, Width, Decimal & Labels for variables
Variable Type: Comma & Dot
Variable Type: Scientific Notation
Variable Type: Date and Time Stamps
Variable Type: Dollar
Variable Type: Custom Currency
Variable Type: String
Variable Type: Restricted Numeric
Defining Values & Labels
Defining Missing Values: Discrete, Range & System-Missing Values
Setting Columns & Alignment
Defining Measures: Scales of Measurement
Section 5: Working with Various File Types in SPSS

This lecture gives an overview of various types of data files that can be opened in SPSS Statistics. 


In this lecture you will learn how to open an Excel data file in SPSS. 


In this lecture you will lean how to open a CSV file type in SPSS using data import wizard. 

Section 6: Independent Sample t-test: Comparing Two Independent Group Means
Independent sample t-test: Defining input options
Independent sample t-test: Interpreting descriptive output (Mean, SD, SE)
Independent Sample t-test: Interpreting Levene's test, t, p, SE & 95% CI
APA Style write-up for Independent Sample t-test
Section 7: Paired Sample t-test: Comparing Differences between Two Correlated Group Means
When to use Paired Sample t-test?
Calculating Paired Sample t-test in SPSS
Interpreting Paired Sample t-test Output
APA Style write-up for Paired Sample t-test
Section 8: One-Way ANOVA: Comparing Differences between More than Two Groups
When to Use One-Way ANOVA?
Calculating One-Way ANOVA in SPSS
Interpreting ANOVA output: Descriptive Statistics
Interpreting Output: ANOVA Summary Table
Doing Post-hoc analysis in ANOVA: Homogeneity of Variance Test & Post-hoc
Trend Analysis & Means Plot in ANOVA
Contrast Analysis in ANOVA
Section 9: Linear Regression: Cause and Effect Analysis of One IV on One DV
What is regression?
When to Use Linear Regression Vs. Multiple Regression?
Defining SPSS Input Options for Linear Regression
Interpreting Linear Regression Output: Variables & Model Summary
Interpreting Linear Regression Output: Constant, B, Beta, SE & t
Section 10: Multiple Regression: Causal Effect of Many IVs on One DV
What is Multiple Regression?
Assumptions of Multiple Regression: Linearity & Testing Linearity in SPSS
Assumptions 2: Independence of Errors/Lack of Autocorrelations & Testing in SPSS
Assumptions 3: Homoscedasticity of Errors & Testing it in SPSS
Assumptions 4: Multivariate Normality & Testing it in SPSS
Assumptions 5: Multicollinearity & Testing it in SPSS
Choosing a Method of Multiple Regression: Enter Method
Choosing a Method of Multiple Regression: Stepwise and Forward Selection Method
Choosing a Method of Multiple Regression: Backward Elimination Method
Running Stepwise and Forward Selection Method of Regression in SPSS
Choosing a Method of Multiple Regression: Remove Method
Section 11: Hierarchical Regression Analysis
What is Hierarchical Regression Analysis and when to use it?
Setting Data and Defining Model in Hierarchical Regression
Refining Model and Detecting Multicollinearity through Correlation Matrix
Taming Bad Data: Using beta, R squared and p values to further refine model
Interpreting the Output of Hierarchical Regression
Section 12: Exploratory Factor Analysis
What is Factor Analysis?
Understanding Latent Variables and Indicators in FA
Sample Researches Using FA in Social Science & Engineering
Historical Origin of FA & Its Application in Test Construction
Exploratory Factor Analysis vs. Confirmatory Factor Analysis (EFA vs. CFA)
Setting Data for Factor Analysis
Understanding "Selection Variable"
Univariate Descriptives & Initial Solutions: Descriptive
Correlation Matrix: Coefficients, Significance, Determinant, KMO & Bartlett's
Understanding Inverse, Reproduced, Anti-Image
Extraction Method: Principle Componenet Analysis
Extraction Method: Principle Axis Factoring
Extraction Method: Maximum Likelihood Estimation
Choosing Correlation vs. Covariance Matrix for Factor Analysis
Interpreting Correlation Matrix & Unrotated Factor Solution
Determining number of factors: Scree Plot vs. Kaiser's eigen value criteria

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Instructor Biography

Dr. Sanjay Singh, Asisstant Professor, Erasmus Mundus WILLPower Fellow

Dr. Sanjay Singh has over 7 years of teaching and research experience and has done his Masters and Doctoral Degree from University of Delhi, India. He have been recipient of Erasmus Mundus-WILLPower fellowship awarded by European Union. During the tenure of his fellowship he studied and worked at the University of Padova, Venice, Italy at the Centre for Risk and Decision-making (CeRD).

He has worked for prestigious institutions like University of Delhi & Indian Institute of Technology, Delhi, and is currently a full time faculty at a premier business school located in Delhi. He has been involved in academic teaching and training for over 7 years along with training and consulting to different companies for data analysis, psychometric assessment, and development of research and analytical skill that can enhance the productivity and growth of people and organizations.

Dr. Singh has trained at reputed organizations like Ernst & Young, DRDO, University of Delhi for IBM SPSS/AMOS and has received excellent rating for his training programs. He has consulted analytics, psychometric and human resource organizations in India and abroad for quantitative project planning, developing customized and culture fair psychometric tests and refinement of quantitative models.He has also consulted students and faculty from reputed institutions like London School of Economics, UK, University of Tallin, Estonia, University of Sydney, Australia, and Faculty of Management Studies, University of Delhi on research and analytics related projects.

Dr. Singh strongly believes that learning can be fun and use of technology in learning can make it even more exciting. As a researcher he loves working at the interface where scientific research, human behaviour and technology meet.

Instructor Biography

Instructor Biography

Heurexler Research, India's Premier Research & Data Science Company

Heurexler Research Pvt. Ltd. is a privately held research company  incorporated in 2013 under Companies Act 1956 & Companies Act 2013 in India. Heurexler Research works at the interface of standard scientific research and expertise and the corporate requirement and receptiveness for the same. At Heurexler we strive to make the serious scientific research a staple for the practical solutions required for addressing the challenges of modern business life and competitive growth. Our company offers customized human resource and testing services & develops new psychometric tests to suit the special needs of our clients. Our core services include dealing with predictive analytics and data science, providing market research, psychometric, training, assessment, and related human resource services. Our team consists of highly qualified research professionals, academicians and experts working with cutting edge quantitative and qualitative research skills.

Our Clients:

Our clients come from all parts of the globe and we have offered our consultancy and training to premium organizations like:

1. Ernst & Young, India

Our IBM SPSS Training Program has been rated 4.5/5 by Ernst & Young India. The detailed feedback report you can refer to testimonial section of our website.

2. University of Delhi, Delhi India

3. DRDO, Chandigarh

4. Scholars from London School of Economics, University of Tallin, Estonia, University of Sydney, Australia

We are the leading research software trainers with our trainers being PhD qualified and published with high impact journals.

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