
Camm/Cochran/Fry/Ohlmann's market-leading
Business Analytics, 5th Edition, published by
Cengage Learning, covers the whole spectrum of analytics, from descriptive and predictive analytics as well as how to create insights that are actionable. Data Mining techniques such as K Nearest Neighbor, Random Forest and Classification Trees are covered.
Step-by-step instructions demonstrate how to use Excel, and the data mining capabilities of R, and Orange to implement advanced analytics concepts. You have the freedom to select your preferred method for teaching concepts using any of today's software choices. Extensive solutions to problems and cases save significant grading time while allowing you to ensure students are mastering the material. In addition, WebAssign, the online learning platform, allows you to you to customize material while strengthening each student's understanding of the concepts.
Question 1 features multiple question types and guides students through the process of interpreting values.
Question 2 links to an Excel data file.
Question 3 is a conceptual question regarding the use and interpretation using descriptive data mining techniques.
Question 4 utilizes special grading to accept a simple linear regression model and guides students through a hypothesis test of the regression parameters.
Question 5 is representative of a test bank question offered.
Question 6 contains a Master It.
Question 7 features grading for a mathematical model and an answer blank format that mimics an Excel spreadsheet.
Question 8 exemplifies use of a simulation model run in Excel. Subsequent confidence intervals are then graded based on the values from their simulation. The solution, which can be visible after students submit responses, displays an Excel spreadsheet and the necessary formulas and instructions needed to run the simulation.
Question 9 allows students to input the appropriate objective function and constraints for a linear programming question and accepts alternative optima as an ordered list.
Question 10 demonstrates how answer blanks can be overlaid onto an image for a seamless experience that mimics textbook presentation.
This demo assignment allows many submissions and allows you to try another version of the same question for practice wherever the problem has randomized values.
This demo assignment allows many submissions and allows you to try another version of the same question for practice wherever the problem has randomized values.
WebAssign provides a wide range of exercises that enable you to:
- Build problem-solving skills (#1-3: Read It, Watch It, and Master It, exercises)
- Develop conceptual understanding (#4-7: Special grading, Test Bank, and Excel spreadsheet exercises)
- Address readiness gaps and assess summative understanding (#8-10: Excel simulation, linear programming exercise, textbook presentation exercise)
The answer key and solutions will display after the first submission for demonstration purposes. Instructors can configure these to display after the due date or after a specified number of submissions. |