2019-2020 Graduate Academic Catalog 
    
    Nov 27, 2021  
2019-2020 Graduate Academic Catalog [ARCHIVED CATALOG]

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MB 6100 - Statistical Thinking and Data Analytics

2 lecture hours 4 lab hours 4 credits
Course Description
Students learn the value of using statistics and data analysis to support decision making in this course. They learn to formulate questions, identify legitimate sources of data, and assess data quality, extract meaningful data from large datasets, and design/use descriptive and predictive models. This course aims at teaching students to transform data into actionable insights. Analytics will focus on relevant economic, customer, and market-related data. Trends in information analytics are also included. (prereq: none) (coreq: MB 6310  or MSN equivalent)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
  • Create a plan that ensures a high degree of transparency in the reporting of local measures against standards and benchmarks
  • Compare current performance to benchmarks and identify gaps
  • Utilize data from organization performance monitoring systems to improve student achievement
  • Create a plan that ensures a high degree of transparency in the reporting of local measures against standards and benchmarks
  • Compare current performance to benchmarks and identify gaps
  • Utilize data from organization performance monitoring systems to improve student achievement
  • Demonstrate how statistics and analytics can be used to identify patterns and analyze problems
  • Determine root cause of a problem and identify the data needed to help understand and address it
  • Apply methods of descriptive inferential, predictive and evaluative statistics to support decision-making and problem resolution
  • Using existing data sources, extract data and convert it into a useful format to support decision-making and goal achievement
  • Identify tools and techniques that support the aggregation and disaggregation of organization performance data to support decision-making on multiple levels
  • Identify data sources and evaluate data quality
  • Using existing data sources, extract data and convert it into a useful format to support decision-making and goal achievement
  • Identify tools and techniques that support the aggregation and dis-aggregation of organization performance data to support decision-making on multiple levels
  • Identify data sources and evaluate data quality
  • Apply multiple techniques to analyze and define the root cause of a problem
  • Assist others in developing a “statistical thinking” mindset and incorporating data analysis in appropriate tasks
  • Make sound decisions and exercise good judgment under conditions of uncertainty
  • Identify methods for reducing uncertainty and making effective decisions under uncertainty
  • Given a scenario, describe the risks to an organization and ways to minimize or mitigate risk

Prerequisites by Topic
  • None

Course Topics
  • No course topics appended

Coordinator
Dr. Katie McCarthy



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