Training Seminar On Data Analytics For Managerial Decision Making

INTRODUCTION

We now live in a data-driven world and effective managerial decision-making relies heavily on the ability to interpret and leverage data. This interactive seminar on Data Analytics for Managerial Decision Making is designed to equip professionals with the skills and knowledge to use data analytics as a powerful decision-support tool. Participants will learn to apply data analytics to support strategic initiatives, inform policy decisions, and guide operational choices. The seminar on Data Analytics for Managerial Decision Making will emphasize the practical application of data analytics in management, focusing on the valid interpretation of findings and the integration of quantitative reasoning into the decision-making process. By the end of this course on Data Analytics for Managerial Decision Making, participants will have greater confidence in using evidence-based information to enhance their managerial decisions.

Course Objectives

By the end of this course on Data Analytics for Managerial Decision Making, participants should be able to:

• Appreciate the role of data analytics in supporting decision-making
• Understand the scope and structure of data analytics
• Apply a variety of data analytics techniques
• Interpret statistical evidence critically and meaningfully
• Identify relevant applications of data analytics in management practice

Duration

5 Days

Who Should Attend

This seminar on Data Analytics for Managerial Decision Making is ideal for a wide range of professionals, particularly:

• Professionals in management support roles
• Analysts who regularly encounter data and analytical information
• Individuals seeking to enhance their decision-making capabilities through data analytics

Course Content

Day One: Setting the Statistical Scene in Management

• Introduction to the quantitative landscape in management
• Thinking statistically about applications in management (identifying KPIs)
• Integrative elements of data analytics
• Understanding data types, quality, and preparation
• Exploratory data analysis using Excel (pivot tables)
• Using summary tables and visual displays to profile sample data

Day Two: Evidence-based Observational Decision Making

• Numeric descriptors to profile numeric sample data
• Measures of central and non-central location
• Quantifying dispersion in sample data
• Examining the distribution of numeric measures (skewness and bimodal)
• Exploring relationships between numeric descriptors
• Conducting breakdown analysis of numeric measures

Day Three: Statistical Decision Making – Drawing Inferences from Sample Data

• Foundations of statistical inference
• Quantifying uncertainty in data with a normal probability distribution
• Importance of sampling in inferential analysis
• Sampling methods (random-based sampling techniques)
• Understanding the sampling distribution concept
• Confidence interval estimation

Day Four: Statistical Decision Making – Drawing Inferences from Hypotheses Testing

• The rationale of hypothesis testing
• Hypothesis testing process and types of errors
• Tests for a single mean in a single population
• Tests of means in two independent populations
• Matched pairs test scenarios
• Comparing means across multiple populations

Day Five: Predictive Decision Making - Statistical Modeling and Data Mining

• Exploiting statistical relationships to build predictive models
• Model building using regression analysis
• Model building process and evaluation of regression models
• Overview of data mining and its evolution
• Applications of descriptive data mining in management
• Applications of predictive (goal-directed) data mining in management

General Notes

• The course is delivered by seasoned trainers with extensive professional experience in their respective fields.
• Training includes practical activities, theoretical knowledge, group work, and case studies.
• Participants receive comprehensive training manuals and additional reference materials.
• A certificate is awarded upon successful course completion.
• Custom-tailored courses to meet specific organizational needs are available. Contact us at training@skillsforafrica.org for more information.
• The training will be conducted at the Skills for Africa Training Institute in Nairobi, Kenya.
• The training fee covers tuition, materials, lunch, and venue. Accommodation and airport transfer can be arranged upon request.
• Payment should be made to our bank account before the training starts, and proof of payment sent to: training@skillsforafrica.org