Unlock Your Research Potential with Advanced SPSS Training
Take your academic journey to the next level with our comprehensive, hands-on SPSS training designed specifically for university students and researchers. Whether you’re tackling your first research project or preparing for advanced postgraduate analyses, our course empowers you with the skills, confidence, and practical experience needed to turn data into meaningful insights.
Learn from expert instructors, work through real-world datasets, and master the tools that top researchers rely on. Transform your academic performance, strengthen your thesis or dissertation, and stand out in your field with advanced SPSS proficiency.
Your success starts with the right skills—let’s build them together.
Session 1
- Binary Regression
- Multinominal Regression
Session 2
- Ordinal Regression
- Poisson Distribution
- Poisson Regression
Session 3
- MANOVA
- MANCOVA
Session 4
- ANCOVA
- MANCOVA
Session 5
- Cluster analysis
- Validity analysis
Session 6
- Bayesian Statistics
- One Sample Normal
- One Sample Binomial
- One Sample Poisson
- Related Samples Normal
- Independent Samples Normal
- Pearson correlation
- Liner Regression
- One-way ANOVA
Session 7
- Loglinear models
- One-way repeated measure ANOVA
Session 8
- Meta-analysis
- Continuous outcome
- Raw data
- Pre-calculated effect size
- Proportional
- Binary outcome
- Raw data
Session 9
- Pre-calculated effect size
- Meta Regression
- Odds Ratio
- Hazard Ratio
- Risk Ratio
Session 10
- Survey Analysis
- Principal components analysis
Session 11
- Explanatory analysis
- Confirmatory analysis
- Coding data
Session 12
- Questionnaire design
- Likert Scale
- Composite
Session 13
- Regression
- Automatic Linear regression
- Linear
- Linear OLS alternative
- Ridge
- Lasso
- Elastic net
- Curve Estimations
- Partial least squares
- Binary logistic
- Multinomial logistic
- Ordinal Probit
- Nonlinear
- Weight estimation
- 2-stage least squares
- Quartile
- Optimal scaling (CATREG)
- Kernel Ridge
Session 14
- Loglinear
- General
- Logit
- Model Selection
- Neural Network
- Multilayer perceptron
- Radial Basis Function
Session 15
- Classify
- Two Step Cluster
- K-Mean Cluster
- Hierarchical Cluster
- Cluster Silhouettes
- Naive Bays
- Tree
- Discriminant
- Ntile analysis
- Nearest neighbour
- ROC analysis
- Dimension
- Factor
- Correspondence analysis
- Optimal scaling
Session 16
- Scale
- Reliability analysis
- Weighted KAPPA
- multi dimensional unfolding (PREFSCAL)
- Multidimensional scaling (PROXSCAL)
- Multidimensional Scaling (ALSCAL)
Additional Session
- Normal Parametric tests
- one sample
- Independent samples
- Related samples
- Quad non-parametric ANOVA
- Legacy dialogs
- chi-square
- Binomial
- Runs
Additional Session
- 1-Smaple K-S
- 2 Independent Samples
- K-independent samples
- 2 related samples
- K-related samples
- Survival
- Life tables
- Kaplan-Meier
- Cox-Regression
- Cox w/Time Dep cov
- Parametric accelerated failure time (AFT) models
- Parametric shared Frailty modelssis Function