Project

To give you practical experience in implementing the quantitative methods taught in this course and to help you see how you can successfully improve business processes using Statistical Thinking, the principle assignments of the class are mini-projects of your own choosing. I wanted it to be this way so that the course would be meaningful to you since you are going to try to improve something that is important to you and not simply work on a case study or word problem assigned by me. This is authentic assessment.

There are four such mini-projects:

1. Mini-Project 1: Descriptive Statistics and Data Visualization.

2. Mini-Project 2: Forecasting or Spreadsheet Modeling

3. Mini-Project 3: Modeling and Design of Experiments.

4. Mini-Project 4: Statistical Inference.

Choosing the right project, the right process to study. Each of the four projects you choose should have these three qualities:

1. Involve a process about which you know something so that you can apply subject matter knowledge. The importance of this cannot be overstated.

2. Allow collection of sufficient relevant data.

3. Provide an opportunity for intervention and improvement.

Recall that the objectives of the course are for students to be able to:

1. Design data collection plans

2. Collect and organize data using Microsoft Excel

3. Analyze that data using Microsoft Excel

4. Arrive at "right answers"

5. Convert "right answers" into business decisions

6. Present their findings persuasively using appropriate data visualization tools and language

In your second project, you will obtain data from some process in your life that can be forecast using the tools of time-series analysis. You will then use the various forecasting methods available to you to "predict the future". You will choose the method that yields the lowest mean absolute deviation (MAD) or mean squared error (MSE) and describe your thought processes as you do so.