Effective Business Decisions using Data Analysis


Effective Business Decisions using Data Analysis

Effective Business Decisions using Data Analysis
14 - 18 يوليو 2024
Kuala Lumpur, ماليزيا

What are the Goals?

By the end of this training course, participants will be able to:

  • Appreciate data analytics in a decision support role
  • Explain the scope and structure of data analytics
  • Apply a cross-section of useful data analytics
  • Interpret meaningfully and critically assess statistical evidence
  • Identify relevant applications of data analytics in practice

Who is this Training Course for?

This training course is suitable to a wide range of professionals but will greatly benefit:

  • Professionals in management support roles
  • Analysts who typically encounter data / analytical information regularly in their work environment
  • Those who seek to derive greater decision making value from data analytics   

Daily Agenda

Day One: 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 Two: 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 Three: 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 Four: 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 Five: 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


الوقت والتاريخ
الأحد، 14 يوليو 2024
البداية - 10:00 ص (Asia/Kuwait)
الخميس، 18 يوليو 2024
النهاية - 10:00 ص (Asia/Kuwait)

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Kuala Lumpur

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