Effective Business Decisions using Data Analysis
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Effective Business Decisions using Data Analysis
Effective Business Decisions using Data Analysis
14 -
18
Jul
2024
Kuala Lumpur,
Malaysia
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
Tickets
Registrations are closed
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