Course description
Every professionals 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; to inform on policy information; and to direct operational decision making.
Upcoming start dates
Upcoming start dates
Suitability - 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
Outcome / Qualification etc.
At the end of the, Effective Business Decisions Using Data Analysis Training course, you will be able to :
- ppreciate 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
Training Course Content
Day 1
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
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
Request info
London Premier Centre
London Premier Centre is a UK leading training provider based in London and specialises in international short courses. Our inspiring, comprehensive portfolio of more than 400 professional development courses and seminars covers a wide range of professions from Administration, Leadership,...