1. Using the Excel document as your data source, enter the scores of the winning and losing teams into your calculator. The winning teams’ scores will be entered into L1 and the losing teams’ scores should be entered in L2. You should check to make sure that your data was entered correctly and check that you have 48 entries for both L1 and L2.
2. Determine the average score for the winners and the average score for the losers. All scores should be rounded to the nearest integer.
Winners - 30
Losers - 16
3. Create a box and whisker chart for both the winners’ and losers’ scores. How do the median scores compare? Remember, in order to construct a box and whisker chart, you will need to find the minimum, median, maximum and the 1st and 3rd quartiles. Make sure that the scales are accurate.
5 number summary
Super Bowl History
4. Compare the Standard Deviations between the winning and losing scores. How are they similar? How are they different? What do they mean?
Losers - 6.8
Winners - 9.8
They both show that the winner's standard are higher than the loser's. Which makes sense as the means are also proportionally the same. It means that around 65% of the winner's scores are between 20.2 and 39.8. Furthermore, around 65% of the loser's data are between 9.2 and 22.8.
5. Could there be a correlation between the Super Bowl number and the score of the game? Calculate the linear regression between the Super Bowl number and the winning score. What is the correlation coefficient? What does that tell us? Passing numbers have increased over the past few years due to changes in rules. Has there been an increase in scores over the past few games? How did you come to that conclusion?
The correlation coefficient of the winners and number of super bowls is .19. This means that the data has very little correlation. The passes have increased but the scores of the games have not. I came to this conclusion by seeing the raw data where the first and last super bowls have 2 points of difference.
6. Calculate the linear regression between the winning team and the losing team. What does the correlation coefficient tell us? Based on your model, if the winning team scores 35 points, how many points will the losing team score? If the losing team scores 12 points, how many will the winning team score?
The correlation coefficient of the losers is .21. This means that the correlation between the losing and winning sides are also very random. If the winning team scores 35 points, the losing team will score 16 points. If the losing score scores 12 points, the winning scores 13.