Data Analytics
Description
There are a number of statistical tools and techniques that are commonly used by organizations to inform decision-making. These tools span numerous business functions and support many different objectives. This intermediate-level course describes, evaluates, and analyzes different statistical techniques and their real-world limitations and benefits. The course features crossover analysis, break-even analysis, cluster analysis, decision tree analysis as well as an introduction to regression.
credits
- PMI PDUs: 5
- Leadership PDUs: 1.5
- Strategic & Business Management PDUs: 1
- Technical PM PDUs: 2.5
- IACET CEUs: 0.5
- HRCI Credits: 5
- SHRM PDCs: 5
features
- Mobile-friendly
- Badge and credit-awarding
- Real-world case studies
- Fully accessible
- Games & Flashcards
- Expert-supported
- Video content
- Audio-enabled
learning Outcomes
- Describe linear programming as finding the "best" solution to a problem
- Explain how crossover analysis is utilized in decision making
- Explain the factors and assumptions involved in break-even analysis
- Apply the standard deviation rule to a special case of normal distributions
- Interpret the results of an ANOVA test
- Describe the various forecasting techniques and the benefits and limitations
- Identify regression analysis applications for purposes of description and prediction
- Describe other statistical techniques (time series analysis, cluster analysis, decision trees) and their real-world application
- Explain the advantages and disadvantages of various statistical techniques
- Choose a statistical technique based on a brief case study