Module 1: Foundations of Multivariate Analysis and Data Screening in SPSS

• Definition of Multivariate Analysis (MVA) and classification of techniques
• Key assumptions of multivariate models: Linearity, Normality, Homoscedasticity, Multicollinearity
• Data cleaning and transformation techniques in SPSS
• Detecting and handling outliers and missing data in SPSS
• Conducting assumption checks using Frequencies, Descriptives, and Explore functions
• Practical session: Importing a dataset, conducting extensive data screening, and preparing the data for MVA in SPSS

Module 2: Multiple Linear Regression and Model Building in SPSS

• Principles of Multiple Linear Regression (MLR) and its assumptions
• Procedures for entering variables: Standard, Hierarchical, and Stepwise methods in SPSS
• Interpreting regression coefficients (B), Standardized Coefficients (β), R², and Adjusted R²
• Identifying and mitigating multicollinearity using Tolerance and VIF statistics
• Testing for interaction terms and moderation effects in SPSS
• Practical session: Building and comparing multiple MLR models, checking diagnostic plots, and interpreting the final solution in SPSS

Module 3: Binary Logistic Regression Analysis in SPSS

• Theoretical foundations of Logistic Regression for categorical outcomes
• Model estimation and interpreting the Logit transformation
• Calculating and interpreting the Odds Ratio (Exp(B))
• Assessing model fit: Hosmer-Lemeshow test and classification tables
• Running and interpreting Binary Logistic Regression in the SPSS dialogue box
• Practical session: Conducting a Binary Logistic Regression, predicting group membership, and analyzing the ROC curve in SPSS

Module 4: Multivariate Analysis of Variance (MANOVA) in SPSS

• Rationale for using MANOVA over multiple ANOVAs
• Assumptions of MANOVA: Normality, Homogeneity of Covariance Matrices (Box's M test)
• Interpreting multivariate test statistics: Wilks' Lambda, Pillai's Trace, Hotelling's Trace
• Follow-up procedures: Discriminant Function Analysis (DFA) and Step-down analysis
• Conducting a MANOVA and interpreting the multivariate output in SPSS
• Practical session: Performing a One-Way MANOVA, assessing assumptions, and determining which DVs contribute most to group separation

Module 5: Discriminant Function Analysis (DFA) using SPSS

• Purpose and application of Discriminant Function Analysis (DFA)
• Deriving and interpreting discriminant functions and canonical correlations
• The classification matrix and calculating hit ratio
• Interpreting structure matrices (loadings) and group centroids
• Cross-validation techniques (Leave-One-Out Classification) in SPSS
• Practical session: Running a DFA, evaluating the predictive accuracy, and interpreting the group classification results in SPSS

Module 6: Exploratory Factor Analysis (EFA) and Dimensionality Reduction in SPSS

• Distinguishing between EFA and Principal Component Analysis (PCA)
• Determining the number of factors: Kaiser criterion, Scree plot, Parallel Analysis
• Factor extraction methods (Principal Axis Factoring vs. Maximum Likelihood)
• Factor rotation techniques: Orthogonal (Varimax) and Oblique (Oblimin)
• Interpreting the rotated factor matrix and calculating factor scores
• Practical session: Performing a full EFA to validate a multi-item scale and saving the resulting factor scores in SPSS

Module 7: Cluster Analysis and Market Segmentation in SPSS

• Goals and applications of Cluster Analysis (CA)
• Hierarchical CA: Measures of similarity/distance and linkage methods
• Non-Hierarchical CA: K-Means Clustering procedure
• Determining the optimal number of clusters and profile interpretation
• Validating and profiling the identified clusters using ANOVA/Chi-square in SPSS
• Practical session: Conducting both Hierarchical and K-Means Cluster Analysis and profiling the resulting segments using descriptive statistics in SPSS

Module 8: Introduction to Survival Analysis (Cox Regression) in SPSS

• Concepts of time-to-event data, censoring, and survival probability
• Non-parametric Survival Analysis: Kaplan-Meier curves and Log-Rank Test
• Introduction to the Cox Proportional Hazards (PH) Regression Model
• Interpreting the Hazard Ratio (Exp(B)) and testing the PH assumption
• Running Kaplan-Meier and Cox Regression analysis in SPSS
• Practical session: Calculating Kaplan-Meier survival probabilities and running a Cox PH model to determine predictors of an event in SPSS

Module 9: Repeated Measures ANOVA and Mixed Models in SPSS

• Rationale for analyzing non-independent (repeated) data
• Univariate Repeated Measures ANOVA: Testing for main effects and interactions
• Assumptions for Repeated Measures: Sphericity (Mauchly's Test) and corrections (e.g., Greenhouse-Geisser)
• Introduction to Mixed Models (Random Intercept/Slope) for complex designs
• Setting up and executing Repeated Measures ANOVA in SPSS
• Practical session: Performing a Two-Way Repeated Measures ANOVA and interpreting the assumption checks and within-subjects effects in SPSS

Module 10: Advanced Reporting, Interpretation, and Presentation of Results

• Best practices for reporting MVA results for journal publication or corporate reports
• Transforming raw SPSS output tables into clear, professional-grade tables
• Visualizing complex relationships: Scatterplot matrices, interaction plots, and classification charts
• Model comparison and selection techniques (AIC, BIC)
• Ethical considerations in the use and reporting of multivariate findings
• Practical session: Running an end-to-end MVA (e.g., Logistic Regression) and producing a concise, publication-ready report and presentation slides based on the SPSS output

Requirements:

·       Participants should be reasonably proficient in English.

·       Applicants must live up to Armstrong Global Institute admission criteria.

Terms and Conditions

1. Discounts: Organizations sponsoring Four Participants will have the 5th attend Free

2. What is catered for by the Course Fees: Fees cater for all requirements for the training – Learning materials, Lunches, Teas, Snacks and Certification. All participants will additionally cater for their travel and accommodation expenses, visa application, insurance, and other personal expenses.

3. Certificate Awarded: Participants are awarded Certificates of Participation at the end of the training.

4. The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.

5. Approval of Course: Our Programs are NITA Approved. Participating organizations can therefore claim reimbursement on fees paid in accordance with NITA Rules.

Booking for Training

Simply send an email to the Training Officer on training@armstrongglobalinstitute.com and we will send you a registration form. We advise you to book early to avoid missing a seat to this training.

Or call us on +254720272325 / +254725012095 / +254724452588

Payment Options

We provide 3 payment options, choose one for your convenience, and kindly make payments at least 5 days before the Training start date to reserve your seat:

1. Groups of 5 People and Above – Cheque Payments to: Armstrong Global Training & Development Center Limited should be paid in advance, 5 days to the training.

2. Invoice: We can send a bill directly to you or your company.

3. Deposit directly into Bank Account (Account details provided upon request)

Cancellation Policy

1. Payment for all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.

2. Participants may cancel attendance 14 days or more prior to the training commencement date.

3. No refunds will be made 14 days or less before the training commencement date. However, participants who are unable to attend may opt to attend a similar training course at a later date or send a substitute participant provided the participation criteria have been met.

Tailor Made Courses

This training course can also be customized for your institution upon request for a minimum of 5 participants. You can have it conducted at our Training Centre or at a convenient location. For further inquiries, please contact us on Tel: +254720272325 / +254725012095 / +254724452588 or Email training@armstrongglobalinstitute.com

Accommodation and Airport Transfer

Accommodation and Airport Transfer is arranged upon request and at extra cost. For reservations contact the Training Officer on Email: training@armstrongglobalinstitute.com or on Tel: +254720272325 / +254725012095 / +254724452588