Effective Business Decisions Using Data Analysis
Select Other "city & date"
Effective Business Decisions Using Data Analysis Course
Introduction:
Every professional strives to make quality decisions. Quality decisions result from a careful and thorough evaluation of relevant information. Often such information is generated through statistical manipulation of data, but few professionals possess quantitative reasoning skills to meaningfully and validly interpret such statistical findings themselves or question the interpretations given by others.
Effective Business Decisions Using Data Analysis Training course will feature the added value that data analytics can offer a professional as a decision support method in management decision-making. It will highlight the usage of data analytics to support strategic initiatives; inform policy information; and direct operational decision-making.
The course will emphasize applications of data analytics in management practice; focus on the valid interpretation of data analytics findings; and build a clearer understanding of how to integrate quantitative reasoning into management decision-making.
Course Objectives:
At the end of the Effective Business Decisions Using Data Analysis Training course, you will be able to:
- appreciate the role of Data Analysis as a decision-support tool
- Explain the scope and structure of the discipline of Statistics
- Understand the importance of data quality in data analysis
- Select an appropriate Data Analysis methodology to apply to specific management situations
- Apply a cross-section of Data Analysis tools and techniques
- Meaningful interpret statistical output to inform decision-making
- Critically assess statistical findings with confidence
- Interact meaningfully and with confidence with Data Analysts
- Initiate with confidence in their Data Analysis projects
- Learn techniques to support strategic initiatives
Who Should Attend?
Effective Business Decisions Using Data Analysis Training course is ideal for:
- 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
Course Outlines:
Setting the Scene and Observational Decision-Making
- Setting the Quantitative Scene
- The Decision Support Role of Quantitative Methods in Management
- "Thinking Statistically" About Applications in Business Practice
- The Elements and Scope of Quantitative Management
- Data and the Importance of Data Quality
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.
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
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
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