Apply fundamentals of statistical analysis, which includes evaluating statisticalinformation, performing data analyses, and interpreting and communicating analytical results. Use the R language for statistical analysis, data visualization and report generation. Topics covered include descriptive statistics, central tendency, exploratory data analysis, probability theory, discrete and continuous distributions, statistical inference, correlation, multiple linear regression, contingency tables, and chi-square tests. Selected contemporary statistical, concepts, such as bootstrapping, are introduced to supplement traditional statistical methods.
In addition, the exercises include fundamental concepts, solution techniques, modeling approaches and applications of decision analytics, with the purpose of introducing you to the most commonly used applied optimization, simulation, and decision analysis techniques for prescriptive analytics in business.
Objectives:
- Perform statistical analyses.
- Interpret and evaluate statistical information.
- Prepare technical reports and use the language R for data analysis.
- Contribute knowledge of fundamental decision analytic concepts along with the skills necessary to perform optimization, simulation, and decision analysis techniques.
- Select appropriate decision analytic modeling techniques given particular business situations.
- Develop and implement decision analytic solutions to address different types of real-world managerial decision problems using analytical modeling software.
- Communicate the results of decision analytic solutions via the delivery of reports and presentation.