Data Analytics for Managerial Decision Making
Course Overview
• Understand the role of data analytics in managerial decision making
• Learn how to apply data analytical methods to real-world business problems
• Develop skills to interpret and critically assess statistical evidence
• Integrate data-driven insights into management decision processes
Training Format:In-class, Virtual, In-house
Location:Lagos, Accra, Nairobi, Kigali
Language:English, French
Nigeria Price:
₦350000
Int'l., (Nigeria) Price:
$1000
Ghana Price:
$4000
Kenya Price:
$5500
Rwanda Price:
$6000
Nigeria Price:₦350000
Int'l., (Nigeria) Price:
$1000
Ghana Price:
$4000
Kenya Price:
$4000
Rwanda Price:
$4000
Nigeria Price: ₦350000
Int'l., (Nigeria) Price:
$1000
Ghana Price: $4000
Kenya Price: $4000
Rwanda Price: $4000
Introduction to Data Analytics in Management
• The quantitative landscape in management
• Thinking statistically about applications in management (identifying KPIs)
• The integrative elements of data analytics
• Data: The raw material of data analytics (types, quality and data preparation)
Exploratory Data Analysis
• Exploratory data analysis using Excel (pivot tables)
• Using summary tables and visual displays to profile sample data
• Numeric descriptors to profile numeric sample data
• Central and non-central location measures
• Quantifying dispersion in sample data
• Examining the distribution of numeric measures (skewness and bimodal)
• Exploring relationships between numeric descriptors
• Breakdown analysis of numeric measures
Statistical Decision Making
• The foundations of statistical inference
• Quantifying uncertainty in data – the normal probability distribution
• The importance of sampling in inferential analysis
• Sampling methods (random-based sampling techniques)
• Understanding the sampling distribution concept
• Confidence interval estimation
• The rationale of hypotheses testing
• The hypothesis testing process and types of errors
• Single population tests (tests for a single mean)
• Two independent population tests of means
• Matched pairs test scenarios
• Comparing means across multiple populations
Predictive Decision Making
• Exploiting statistical relationships to build prediction-based models
• Model building using regression analysis
• Model building process – the rationale and evaluation of regression models
• Data mining overview – its evolution
• Descriptive data mining – applications in management
• Predictive (goal-directed) data mining – management applications
Who should attend:
• Professionals in management support roles
• Analysts who regularly encounter data and analytical information in their work
• Those seeking to derive greater decision-making value from data analytics
1ST BATCH: Tuesday, February 3, 2026 — Friday, February 6, 2026.
2ND BATCH: Tuesday, May 26, 2026 — Friday, May 29, 2026.
3RD BATCH: Tuesday, September 22, 2026 — Friday, September 25, 2026.
The training methodology integrates lectures, interactive discussions, collaborative group exercises, and
illustrative examples. Participants will acquire a blend of theoretical insights and hands-on practical
experience, emphasizing the application of learned techniques. This approach ensures that attendees return
to their professional environments equipped with both the competence and self-assurance to effectively
implement the acquired skills in their responsibilities.
