Data Science: An Introduction/Thinking Like a Scientist

 Data Science: An Introduction  Chapter 09: Thinking Like a Scientist



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Chapter Summary
When a data scientist thinks like a scientist, they think in terms of validity and reproducibility. The task is to set up tests that eliminate alternative explanations in such a way that any observer would come to the same conclusion if they did the work themselves.

Assignment/Exercise
This Project #2, which spans four chapters. Assemble into groups of 3 or 4 students. A group of three may not have the same members as the group for Project #1. A group of four may have no more than two students repeating from the group from the Project #1. This group will do the entire project together. Note: Your group can specialize on tasks, but everyone needs to participate in all phases of the assignment. Also, the chapters covered to this point do not teach you everything you need to know to do this assignment. Please do the best you can with what you know. This assignment is not just to show the instructor how much of the previous chapters you have learned, but the assignment is a learning experience in and of itself. The assignment is designed for the students to discover knowledge not contained in the chapters.
 * 1) Replicate Galileo's "inclined plane" experiment.  Start by designing the research and write down your plan. List materials needed, specify methods to be used, identify variables to be measured, create data recording sheets, etc.
 * 2) Conduct the experiment according to the design. Take pictures. Record your data results.
 * 3) Enter the data into R.  Use R to produce tables and draw plots of your data.  See if you can draw the theoretical curve Galileo was trying to discover on your data plots.
 * 4) Prepare a slide presentation that includes a description of your methods, pictures of your apparatus, a table of your raw data, a table of your analyzed results, plots of your results, a list of several things the group learned on its own about data science during the course of this project.

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