Course Schedules

Classroom 8 Sessions
Online / Live
Live

No dates scheduled

Introduction

Data Analytics for Managerial Decision Making training course equips managers with the skills to leverage data for strategic and operational decisions. Managers increasingly rely on evidence-based insights to navigate complex business challenges. This course provides a practical understanding of data analytics from a managerial perspective, focusing on interpreting, analyzing, and applying statistical information to real-world scenarios.

Participants will gain hands-on experience with tools and techniques for analyzing data, uncovering patterns, and supporting decision-making. Emphasis is placed on accurate interpretation of analytical findings, ensuring managers can confidently translate data into actionable insights. By the end of this training course, delegates will be able to integrate data analytics into daily managerial processes, enhance operational efficiency, and improve organizational outcomes.

What are the Goals?

Attending this Data Analytics for Managerial Decision Making training course will enable delegates to apply data-driven techniques effectively in managerial contexts. Participants will learn how to critically evaluate statistical data and use analytics tools to support informed decisions.

  • Recognize the power of data analytics as a decision-support tool in management
  • Assess the reliability and validity of statistically-generated business information
  • Identify appropriate data analytic tools for various management scenarios
  • Interpret statistical evidence meaningfully and accurately in decision-making
  • Communicate effectively with data analytics professionals and teams

Who is this Training Course for?

This Data Analytics Training Course is ideal for managers and professionals responsible for driving organizational performance through informed decisions. It also suits consultants and support personnel involved in business strategy and operational improvements.

  • HR Managers overseeing workforce analytics and performance metrics
  • Marketing Managers analyzing customer insights and campaign results
  • Operations and Logistics Managers optimizing processes and efficiency
  • Financial Managers interpreting financial data for strategic planning
  • Policy Support Personnel contributing to data-driven policy decisions
  • Engineers and Technical Specialists using analytics in project management

How will this Training Course be Presented?

The course combines interactive lectures, practical exercises, and case studies to strengthen managerial decision-making skills through data analytics. Participants will engage in hands-on data analysis using tools like Excel and explore real-world scenarios to develop evidence-based insights.

Practical exercises cover data preparation, exploratory data analysis, and interpretation of statistical outputs. Delegates will also practice predictive modeling, regression analysis, and data mining techniques applicable to business contexts. By integrating experiential learning with theoretical concepts, this training course ensures participants develop both analytical capabilities and decision-making confidence.

Course Content

Day 1

Setting the Statistical Scene in Management

  • Introduction; 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 using excel (pivot tables)
  • Using summary tables and visual displays to profile sample data
Day 2

Evidence-based Observational Decision Making

  • Numeric descriptors to profile numeric sample data
  • Central and non-central location measures
  • Quantifying dispersion in sample data
  • Examine the distribution of numeric measures (skewness and bimodal)
  • Exploring relationships between numeric descriptors
  • Breakdown analysis of numeric measures
Day 3

Statistical Decision Making – Drawing Inferences from Sample Data

  • 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
Day 4

Statistical Decision Making – Drawing Inferences from Hypotheses Testing

  • 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
Day 5

Predictive Decision Making - Statistical Modeling and Data Mining

  • 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

The Certificate

Recognition
  • Anderson Certificate of Completion for delegates who attend and complete the training course
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