ThinkSharp Case Library

Alphabetical	Discipline	Industry
Paving the Way Students create a mix of raw materials to make asphalt that meets government constraints and costs less than all other such mixes. After becoming familiar with the mixing process and requirements, students model the problem through algebra, and are introduced to linear programming through a tutorial. After the tutorial, students formulate a linear programming problem and download LINDO software to solve it. View Paving the Way Demo	Optimization 1	Engineering
Insuring Your Success Students decide how to hire employees and assign them jobs within an insurance company in a way that maximizes the expected return on those newly hired employees. Students typically apply a trial and error process, before they are led to steepest ascent algorithm and dynamic programming, both of which require arithmetic, ordering and numerical methods. View Insuring Your Success Demo	Optimization 1	Business
Schedule This! Students schedule make-up exams for 20 students in 10 different subjects so that no student has a conflict. Questions lead students to "discover" a solution using a chromatic algorithm - a simple method using number ordering, and arithmetic. View Schedule This! Demo	Optimization 2 & Network Analysis	Education
Air Tragedy: Surviving the Crash Students predict survival probabilities as they analyze airplane crash data. View Air Tragedy Demo	Statistical and Graphical Analysis	Statistics
Setting the Standard Part 1 Students re-create and extend medical research for the standardization of care in the ICU as they learn state vectors and standard deviation. View Setting the Standard Part 1 Demo	Statistical and Graphical Analysis	Statistics
Setting the Standard Part 2 Students further this landmark research as they learn glyphs. View Setting the Standard Part 2 Demo	Statistical and Graphical Analysis	Statistics
A Picture of Recovery Students determine the advantages of scar removal for burn victims as they learn a powerful, graphic technique for multivariate data analysis. View A Picture of Recovery Demo	Statistical and Graphical Analysis,Nursing and Allied Health	Triage and Trauma Care
The Great Cover Up Students find the least expensive way to cover 10 plants with covers of three different sizes in this clever disguise for a real-life military problem. Students learn how to use a combinatorial analysis to distinguish between exhaustion and dynamic programming as the best method for solving problems. View The Great Cover Up Demo	Optimization 1	Military
Networking Your Health Students find the least expensive way to connect hospitals with a wide area network. Questions lead students to "discover" the Kruskal method - a simple algorithm using ordering and arithmetic. View Networking Your Health Demo	Optimization 2,Network Analysis	Triage and Trauma Care
ECMO 2: Newborn Hope Students create a testing strategy for a heroic therapy that could save lives of newborns. Student learn the benefits and risks of a balanced randomized design test and the probability-based adaptive design test. Student learn simple and conditional probability as they grapple with ethical vs. scientific issues. View ECMO 2 demo	Statistical and Graphical Analysis	Triage and Trauma Care
AZT: The Wonder Drug? Student determine the best testing strategy for the AIDS drug AZT. Students learn the procedures for the balanced randomized design test and the probability-based adaptive design test, and see how math can be at the heart of controversy. View AZT demo	Testing Analysis	Research and Development
Scoring for Life Students create indices using arithmetic and normalization to score the injuries of trauma patients. Using the Injury Severity Score as a a model, student are given examples of injured patients to test their indices, and learn how hospitals score their patients. View Scoring for Life	Nursing and Allied Health	Triage and Trauma Care
ECMO 1: Newborn Hope Students determine criteria for assigning newborns to heart lung bypass surgery as they learn exploratory data analysis techniques. View ECMO 1 demo	Statistical and Graphical Analysis,Decision Analysis 1	Triage and Trauma Care
Taking it to the Hoop Students create indices using arithmetic and normalization to score the performance of the NCAA basketball tournament seeding committees. Students answer questions featuring exciting basketball footage and evaluate results to test and redefine their indices. View Taking it to the Hoop Demo	Testing Analysis	Athletics
Fighting Time Students find the best location for a new firehouse. Students compare their method for finding the location to the Dijkstra method - an efficient method that uses addition and ordering to find the quickest route from one location to all other locations. View Fighting Time Demo	Optimization 2,Network Analysis	Triage and Trauma Care
Search for Oil Students identify the best order to drill several different sites for oil. Questions demonstrate the advantages of the "bang for the buck" method as well as the computation of average cost. Students see how these methods apply to medical diagnosing and even auto repairs. View Search for Oil Demo	Decision Analysis 1 & Optimization 2	Engineering
Power Student create an emergency plan that distributes electricity from one Texas city to seven others. Following a tutorial on the Dijkstra method, students are given a second chance to create a plan using this efficient method that requires on arithmetic operations. View Power Demo	Network Analysis	Resource Management
Securing the Nation Students schedule security guards at a top secret government facility so that the least number of guards can be hired. Students use algebraic notation to model the problem. The best model is a very interesting algebra representation. Linear programming is introduced as the preferred method for solving this problem. Hints and LINDO software are provided to help students model and solve the problem. View Securing the Nation Demo	Optimization 1	Military
Deciding Factors Students judge the achievements of several candidates for a scholar athlete award. After using a method of their choice to rank the candidates, students are introduced to the analytical hierarchy process (AHP). Following a tutorial on AHP, students use a spreadsheet to apply the method on their own. This lesson will take approximately 80 minutes. View Deciding Factors Demo	Decision Analysis 1	Athletics
Race to the Fire: Part 1 - 5 Students analyze and draw conclusions from traffic data to find the quickest route to a fire scene. Each part focuses on a different method for solving this and other quickest route problems. The lessons cover trial and error, inspection, greedy and exhaustion methods, the branch and bound method, dynamic programming, and Dijkstra's method. These lessons will take approximately 3 hours. View Race to the Fire: Part 1 Demo	Unknown	Triage and Trauma Care
A Line on Efficiency Students are presented with limited data and asked how many postal clerks are needed to keep a customer line from growing too long. After an attempt using a method of their own, students are introduced to simulation. Following a tutorial explaining simulation, students apply the method to the post office problem and answer a series of questions checking their application. This lesson will take approximately 45 minutes. In addition to this case study, module includes the simulation tutorial and assessment. No Time to Wait Demo	Decision Analysis 1	Resource Management