2) Poster/Visual Representation
a. Should represent your data in an easy to read an accurate way.
b. Should be clear and focused on a few concepts
c. DOES NOT have to incorporate all of the data you collected/found for your project. You may focus on the more interesting aspects.
d. Needs to be either printed and readable or e-mailed to be before we present on Tuesday, May 31 so that we can display on the screen.
3) Report of Data and Analysis. The following must be included in your discussion:
a. How you collected your data:
i. If a survey, make sure to include a copy of the final survey. Also include how you conducted the survey and problems that might have arisen in the collection of the data (underrepresentation, collection of skewed data, etc.)
ii. If you found the data somewhere else, give the source as well as any discussion of how they collected the data. Make sure to find any faults with how the data has been collected.
b. Provide the data you are analyzing
i. If your own data, give a table or some way of showing all the data in a way I can see it all.
ii. If found online, provide a link to the data, or a table of the pieces you used.
c. Provide any relevant statistical analyses. Things to consider: correlation, margin of error or confidence intervals, outliers, five points, population means, or any other important areas that work for your data. Walk me through the important pieces and explain why you did the analysis that you did. If necessary, include a null and alternative hypothesis. Include all r code and graphs that you find that are relevant
d. Explain what all of the analysis means. Explain what your null and alternative hypothesis represent and whether or not we can reject our null hypothesis. What interesting connections can you make through your data? What does your data show? Include a full explanation of what your data shows.
e. If you were to redo this experiment, what would you do differently? What worked well and what should be different?