MAT 273 — Applied Statistics: PROJECT I
This past couple of weeks you have just studied the topics of mean, median, mode, quartiles and standard deviation. Now, we are going to use these mathematical concepts to analyze the weights of the Tiffin University football team. Attached is a roster of the players with their weights, and an electronic form of this data is available on the course webpage.
Find your own personal sample of 30 players by starting at the player named in the email that accompanied this assignment. Start counting with the next person on the list, and take every third person on the list until you get 30 people. (Jump to the top of the table if you run out.)
Compute the five-number summary using the sample data above and then construct a box-and-whisker plot for the data. Draw the graph neatly and accurately by hand. (For online submission, submit a scan or picture.)
Calculate the mean and standard deviation for the sample data.
Use the mean and standard deviation from Part 3 to create an Empirical Rule graph (normal curve). Draw the graph neatly and accurately by hand. Compare the curve to the box and whisker plot to determine if the data “roughly” follows the Empirical Rule. (For online submission, submit a scan or picture.)
The population mean for the entire team is 221.5 pounds and population standard deviation for the entire team is 46.2 pounds. Compare these to the results for step 3. Do your sample statistics fairly represent the population parameters?
Report your findings:
In addition to submitting all work and calculations (whether done by hand or on Excel), you are to submit a word-processed 6-paragraph summary of the assignment and your findings. The summary should be formatted with one paragraph for the introduction , one paragraph of analysis/interpretation for each of steps two through five listed above, and a one-paragraph conclusion. The summary should not detail your method of calculations, rather it should report and interpret the results of your calculations and what they mean. Submit the data, the calculations, the graphs, and the analysis paper to Moodle or to the instructor on or before the due date.