Effective Business Decisions Using Data Analysis
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Effective Business Decisions Using Data Analysis Course
Introduction:
In the pursuit of professional excellence, making high-quality decisions is a top priority. Such decisions are the result of a meticulous and comprehensive evaluation of relevant information. In today's data-driven world, much of this information is derived from statistical analysis. However, many professionals lack the quantitative reasoning skills necessary to interpret statistical findings accurately or challenge existing interpretations.
The Effective Business Decisions Using Data Analysis Training course aims to address this gap by highlighting the value that data analytics brings as a decision support method in management decision-making. This course will demonstrate how data analytics can enhance strategic initiatives, provide valuable insights for policy formulation, and guide operational decision-making.
Throughout the course, the emphasis will be on practical applications of data analytics in real-world management scenarios. Participants will gain a deeper understanding of how to interpret data analytics findings effectively and derive meaningful insights. Moreover, they will learn how to integrate quantitative reasoning seamlessly into their decision-making processes.
Join us in this course as we unlock the power of data analysis for effective business decision-making. Through interactive sessions and practical exercises, participants will develop the skills and confidence to leverage data analytics as a strategic tool. By the end of the course, participants will possess a clearer understanding of how to harness data analytics to inform decision-making, drive organizational success, and gain a competitive edge in today's data-centric business landscape.
Don't miss this opportunity to enhance your decision-making abilities. Enroll in the Effective Business Decisions Using Data Analysis Training course and empower yourself to make informed, data-driven decisions that propel your professional growth and contribute to your organization's success.
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