Tools of Data Analysis
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.
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.
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
0.5 IACET CEUs
5 HRCI Credits
5 SHRM PDCs
5 ATD CI Credits
5 PMI PDUs:
2.5 Ways of Working PDUs
1.5 Power Skills PDUs
1 Business Acumen PDUs
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
Refund Policy
You may request a refund up to 7 days from the purchase date. The registration fee will only be refunded if less than 10% of the course has been completed. Completion percentage can be viewed on the Course Progress page from within the course.
Notes
Estimated time to complete: 5 hours
Access Time: 90 days
This course includes an “Ask the Expert” feature. You can use this feature to submit questions about course content. A subject matter expert will provide guidance or point you to additional resources for the topics you’re studying. Questions are answered as quickly as possible and usually within 24 hours.