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. 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