A project where the student will collect and analyze data relating to whether renewable resources (wind and air) are really cheaper and more effective than coal in the state of Indiana. The purpose of this document is to outline how the student can get started on this project. Students are encouraged to start work on this project before the beginning of the last module. 1. Determine a question of interest which involves quantifiable data. The best place to start is in your environment that you deal with every day. Many examples of these types of questions are also given throughout the course. At the very least, you should start (at the beginning of this class) thinking about an idea. The students will see many examples of where the Professor of the class has analyzed data she has collected just to try to investigate a topic of his interest. 2. Collect data. In the idea above, the student should identify the dependent variable and those things which may likely affect the dependent variable. The student must have 1 dependent variable and at least 2 independent variables and collect at least 30 observations for their data. In past versions of this course, many students have used data from their work or have collected data from surveying other students or people at their work. 3. Analyze the data using the tools developed in this course and submit a written analysis for the student project. Linear Progression, rule of error, histograms, ect… The student will have multiple examples of similar types of analysis and are encouraged to ask questions. Even though the last module of the course does not start util later in the course, the student should work on the project as the course progresses and not wait until the last module begins. Please ask questions if you do not understand!
regards to the osmosis of pieces into lumps. Mill operator recognizes pieces and lumps of data, the differentiation being that a piece is comprised of various pieces of data. It is fascinating to take note of that while there is a limited ability to recall lumps of data, how much pieces in every one of those lumps can change broadly (Miller, 1956). Anyway it’s anything but a straightforward instance of having the memorable option huge pieces right away, somewhat that as each piece turns out to be more natural, it very well may be acclimatized into a lump, which is then recollected itself. Recoding is the interaction by which individual pieces are ‘recoded’ and allocated to lumps. Consequently the ends that can be drawn from Miller’s unique work is that, while there is an acknowledged breaking point to the quantity of pieces of data that can be put away in prompt (present moment) memory, how much data inside every one of those lumps can be very high, without unfavorably influencing the review of similar number