📊 Tobit Research Consulting
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Download session materials, slides and handouts from all our postgraduate training series
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Postgraduate · September 2026
Postgraduate Research Training SeriesMaster Your Research Journey
🕘 9:30 AM – 1:00 PM
📅 3 Sessions
🌐 Online
📅 19th & 26th September, 3rd October 2026
🟢 Series In Progress
Enrollment Closed · 18th September
19th September 2026
Session 1: Research Methodology · Completed
⌄
- Research Design & Philosophy: Selecting an appropriate research design and philosophical orientation, including positivism, interpretivism and pragmatism, in line with the research problem, objectives and methodological approach.
- Target Population, Sampling & Sample Size: Identifying the appropriate target population, developing a sampling framework, selecting probability or non-probability sampling techniques, and determining a scientifically justified sample size.
- Data Collection Tools & Techniques: Designing and selecting questionnaires, interview guides, observation schedules and document review tools that align with the study objectives and variables.
- Pilot Testing, Reliability & Validity: Conducting pilot studies and applying suitable procedures to establish reliability, validity, credibility and the overall quality of study measures.
- Data Analysis Procedures: Planning quantitative and qualitative analysis, including descriptive statistics, inferential analysis, hypothesis testing, thematic analysis and interpretation of findings.
- Research Ethics & Academic Integrity: Applying informed consent, confidentiality, voluntary participation, data protection, research approvals, responsible citation and academic integrity standards.
26th September 2026
Session 2: Data Entry & Analysis · Completed
⌄
- Demographic Analysis: Analysing respondents’ background characteristics to describe the study sample and provide context for interpreting findings.
- Descriptive Analysis: Summarising study variables using frequencies, percentages, means, standard deviations and other descriptive statistics.
- Pilot Testing, Validity & Reliability: Evaluating instruments and scales using pilot data, Cronbach’s Alpha and appropriate validity tests.
- Diagnostic Tests: Testing normality, multicollinearity, homoscedasticity, linearity and autocorrelation before subsequent statistical analysis.
- Correlation Analysis: Examining the strength, direction and significance of relationships using Pearson or Spearman correlation.
- Regression Analysis: Estimating the influence of independent variables on a dependent variable and interpreting model fit, coefficients and statistical significance.
- Hypothesis Testing: Applying suitable statistical procedures, significance levels, p-values and decision criteria.
3rd October 2026
Session 3: Report Writing & Discussions · Upcoming
⌄
- Research Report Writing: Presenting findings clearly and logically while maintaining consistency with the objectives, questions, methodology and institutional requirements.
- Interpretation & Discussion of Results: Relating statistical and qualitative findings to the objectives, theories and previous studies while explaining agreements, contradictions and significance.
- Conclusions: Developing evidence-based conclusions that directly respond to the research objectives and major findings.
- Recommendations: Formulating practical, policy, managerial or scholarly recommendations supported by the study findings.
- Areas for Further Research: Identifying unresolved issues, methodological limitations and emerging gaps for future investigation.
📁 Session materials will be added after the training.
SPSS · July 2026
Postgraduate SPSS Training SeriesMaster Your Data Analysis Journey
🕘 9:30 AM – 1:00 PM
📅 3 Sessions
🌐 Online
📅 4th, 11th, 18th July 2026
💳 Ksh 10,000 (Deposit Ksh 5,000)
✅ Series Completed
4th July 2026
Session 1: Introduction to Basic SPSS
⌄
- Basic feature of SPSS and Data Management - Preparation of dataset and direct entry, Direct entry and importing values, Data coding and labelling, Splitting Files and Merging of Data sets
- Descriptive Statistics - Frequency tables, Graphs, Charts, Custom tables
- Transformation of Data - Recode into same variable, Recode into Different variables, Compute (logs, lag, averages, sum, products etc)
11th July 2026
Session 2: Intermediate SPSS
⌄
- Pilot Testing - Reliability and Validity test: Cronbach Alpha, KMO and Bartlet test; Factor Analysis: Communalities, Factor loadings
- Diagnostic Testing - Normality test, Multicollinearity test, linearity test, Heteroscedasticity test, Autocorrelation
18th July 2026
Session 3: Advanced SPSS
⌄
- Correlation - Pearson correlation, Interpretation of correlation coefficients
- Regression - Simple logistic regression, Multinomial logistic regression
- Hypothesis Testing - Using Regression results
📁 Session materials coming soon.
Postgraduate · May 2026
Postgraduate Research Training SeriesResearch Proposal, Thesis Writing & Defense
🕘 9:00 AM – 1:00 PM
📅 3 Sessions
🌐 Online
📅 16th, 23rd, 30th May 2026
✅ Series Completed
16th May 2026
Session 1: Concept Paper
⌄
Introduction to concept paper writing, structuring research ideas, identifying research gaps and formulating research objectives.
23rd May 2026
Session 2: Research Proposal — Chapters 1, 2 & 3
⌄
- Chapter 1: Introduction
- Chapter 2: Literature Review
- Chapter 3: Methodology & Thesis Defense Preparation
30th May 2026
Session 3: Thesis Writing — Chapters 4 & 5
⌄
- Chapter 4: Data Analysis & Presentation — Understanding the purpose of Chapter 4, organising and structuring results/findings, quantitative data (tables, figures, charts), qualitative data (themes, categories, coding, narrative presentation)
- Chapter 5: Discussion, Conclusion & Recommendations — The difference between results and discussion, interpreting and making meaning from findings, linking findings back to the literature review (Chapter 2)
SPSS · March 2026
Postgraduate SPSS Training SeriesMaster Your Data Analysis Journey
🕘 9:30 AM – 1:00 PM
📅 3 Sessions
🌐 Online
📞 0728 430 728
✅ Series Completed
14th March 2026
Session 1: Introduction to Basic SPSS
⌄
- Basic feature of SPSS and Data Management - Preparation of dataset and direct entry, Direct entry and importing values, Data coding and labelling, Splitting Files and Merging of Data sets
- Descriptive Statistics - Frequency tables, Graphs, Charts, Custom tables
- Pre-test Diagnostic - Normality: Graphical(Histogram), Skewness & Kurtosis, Smirnov Kolmogorov test and Shapiro Wilk test, Multicollinearity: Variance Inflation factor(VIF) and Tolerance
- Regression and Correlation - Formulation of Hypothesis, Beta Coefficients, Interpretation of P-Values, Interpretation of t-statistics, R squared and Adjusted R squared, F statistic
21st March 2026
Session 2: Intermediate SPSS
⌄
- Post-test Diagnostic - Linearity: Scatter plots and compare means, Heteroscedasticity: Glejser test, Autocorrelation/serial correlation - Durbin Watson
- Hypothesis testing using Parametric tests - T tests (Independent t-test, Paired t-test), Z test, Anova
- Hypothesis testing using Non Parametric tests - Chi-Square test (Cross-tabulation), Man Whitney U-test (2k independent Samples), Kruskal Wallis H-test (K independent Samples)
- Transformation of Data - Recode into same variable, Recode into Different variables, Compute (logs, lag, averages, sum, products etc)
28th March 2026
Session 3: Advanced SPSS
⌄
- Categorical Regression analysis - Binary logistic regression, Multinomial logistic regression
- Reliability and Validity test - Cronbach Alpha, KMO and Bartlet test
- Factor Analysis - Communalities, Factor loadings, Scree Plots
📁 Session materials coming soon.
Postgraduate · February 2026
Postgraduate Training SeriesResearch Proposal, Thesis Writing & Defense
🕘 9:00 AM – 1:00 PM
📅 3 Sessions
🌐 Online
📅 14th, 21st, 28th Feb 2026
✅ Series Completed
14th Feb 2026
Session 1: Concept Paper
⌄
Introduction to concept paper writing, structuring research ideas, identifying research gaps and formulating research objectives.
21st Feb 2026
Session 2: Research Proposal — Chapters 1, 2 & 3
⌄
- Chapter 1: Introduction
- Chapter 2: Literature Review
- Chapter 3: Methodology & Thesis Defense Preparation
28th Feb 2026
Session 3: Thesis Writing — Chapters 4 & 5
⌄
- Chapter 4: Data Analysis & Presentation — Understanding the purpose of Chapter 4, organising and structuring results/findings, quantitative data (tables, figures, charts), qualitative data (themes, categories, coding, narrative presentation)
- Chapter 5: Discussion, Conclusion & Recommendations — The difference between results and discussion, interpreting and making meaning from findings, linking findings back to the literature review (Chapter 2)
