Describe your topic. (Include a brief informative description in the title of your posting.) The topic will be similar to the example; however, instead of using the 400 meter dash, I would like to use the 100 meter dash.
Provide your data and cite your source. The data that I would like to use will be the Men’s Olympic gold medal winning times from 1960-2016 of .The data source must be cited.
Collect all data points (Year, Winning time from 1960-2016) and label them clearly on the scatterplot.
Plot the points (x, y) to obtain a scatterplot. (Use an appropriate scale on the horizontal and vertical axes and be sure to label carefully.)
Find the line of best fit (regression line) and graph it on the scatterplot.
State the equation of the line.
State the slope of the line of best fit.
Carefully interpret the meaning of the slope in a sentence or two.
Find and state the value of r2, the coefficient of determination
Find and state the value of R, the correlation coefficient.
Discuss your findings in a few sentences. Is r positive or negative? Why? Is a line a good curve to fit to this data? Why or why not? Is the linear relationship very strong, moderately strong, weak, or nonexistent?
Choose a value of interest and use the line of best fit to make an estimate or prediction. Show calculation work.
Write a brief narrative of a paragraph or two. Summarize your findings and be sure to mention any aspect of the linear model project (topic, data, scatterplot, line, r, or estimate, etc.) that you found particularly important or interesting.
You may submit all of your project in one document or a combination of documents, which may consist of word processing documents or spreadsheets or scanned handwritten work, provided it is clearly labeled where each task can be found. Be sure to include your name. Projects are graded on the basis of