• BAS 340: Exper Methods/Process Improv

  3.00 Credits

  The University of Tennessee - Knoxville

  
  Statistical methods for process improvement. Special/common cause model of variation directed towards understanding sources of variation affecting process operations. Strategies of process experimentation, including randomization, blocking, sequential experimentation, and replication. Use of statistical computing software.(RE) Prerequisite(s): Statistics 201 or 207 or 251.
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• BAS 370S: Search Advertisng Optimization

  3.00 Credits

  The University of Tennessee - Knoxville

  
  Creating, managing, and optimizing Google Ads search advertising campaigns for a local nonprofit. Fundamentals of online advertising metrics and best practices for data-driven improvement of campaigns. Emphasis on communicating data insights to a non-technical audience. Assessment takes place via official Google Ads certification exams, allowing for the option of obtaining Google Ads certifications. (RE) Prerequisite(s): STAT 201 or STAT 207 or STAT 251. Comment(s): Course is intended for juniors or seniors in marketing or business analytics. Registration Permission: Consent of instructor.
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• BAS 454: Stats for Business Analytics

  3.00 Credits

  The University of Tennessee - Knoxville

  
  Application of statistical tools in the context of business problems. Data management, ANOVA, regression, predictive modeling, model performance. Use of SAS software. Preparation for SAS certification exam.(RE) Prerequisite(s): 320 with grade of C or better or consent of instructor.
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• BAS 464: Operations Analytics

  3.00 Credits

  The University of Tennessee - Knoxville

  
  Operations Analytics focuses on data-driven decision making in operations management. Through a case-based, interactive, learning-by-doing approach, students learn a systematic set of analytics methodologies and apply various analytics tools such as spreadsheets, data visualization, optimization, and simulation, to make important operations decisions from large datasets. (RE) Prerequisite: BAS 310 or SCM 309 or SCM 312 with a grade of C or better.
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• BAS 471: Statistical Methods

  3.00 Credits

  The University of Tennessee - Knoxville

  
  Numeric and graphic description of data, probability and probability distributions, simulation, and sampling distributions. Estimation and hypothesis testing for one and two samples, parametric and nonparametric approaches, bootstrapping, and randomization tests. Multiple linear regression review and further issues, diagnostics and validation, and analysis of count data. Data Screening. Use of SAS and other statistical software.(RE) Prerequisite(s): 320 with grade of C or better.
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• BAS 474: Data Mining/Bus Analytics

  3.00 Credits

  The University of Tennessee - Knoxville

  
  Understanding and application of data mining methods. Data preparation, exploratory data analysis and visualization, cluster analysis, logistic regression, decision trees, neural networks, association rules, model assessment, and other topics. Applications to real world data. Use of standard computer packages.(RE) Prerequisite(s): 320 with grade of C or better.
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• BAS 475: Applied Time Series/Forecast

  3.00 Credits

  The University of Tennessee - Knoxville

  
  Model building techniques for linear time series models, practical methods for univariate time series forecasting, Box-Jenkins forecasting methods, forecasting based on exponential smoothing, autoregression and stepwise autoregression, and forecasting from regression models. Use of standard computing packages. Major writing requirement.(RE) Prerequisite(s): 471 or consent of instructor.
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• BAS 476: Data Engineering/Visualization

  3.00 Credits

  The University of Tennessee - Knoxville

  
  Fundamentals of programming using Python with particular focus on data preparation, visualization, and data understanding. Topics include but are not limited to reading data, object-oriented programming, loops, conditional processing, aggregating, merging, and dynamic visualization. Experience gained in producing repeatable data products in Python that automatically ingest, process, and display data in interactive plots. (RE) Prerequisite(s): BAS 474 with a grade of B- or better.
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• BAS 479: Capstone/Business Analytics

  3.00 Credits

  The University of Tennessee - Knoxville

  
  Case studies in business analytics illustrating various aspects of descriptive, predictive, and prescriptive modeling. Strong emphasis on data preparation and statistical programming using SQL, R, and/or other standard software along with writing and presentation skills.(RE) Prerequisite(s): 474 and Information Management 342.
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• BAS 483: Special Topics in Statistics

  1.00 - 3.00 Credits

  The University of Tennessee - Knoxville

  
  Topics vary.Repeatability: May be repeated. Maximum 6 hours.Registration Permission: Consent of instructor.
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