Assignment 2

Assignment 2
Jeff Hessburg
2/21/2017
GEOG 370

PART I
For this assignment, I will be comparing two bike race teams who competed in the TOUR de GEOGRAPHIA; Team ASTANA and Team TOBLER The comparisons will inlude the range, mean, median, mode, kurtosis, skewness, and standard deviation, of the race times for each team. After analyzing the calculations, I will determine which team I would rather invest in, to make the most money.

The Results:

Range- The range is a calculation of the largest value subracted by the smallest value. For this example, the range can be explained by how much time faster the first person on each time finished compared to the slowest. The difference between the fastest and slowest person is much great on team Tobler than team Astana.
Team ASTANA=1 hr 10 min
Team TOBLER=31 min

Mean- The mean is the average of all of the numbers. To calculate, all of the times are added up then divided by the total number of times. for this example, the mean is the average time the bikers on each team finished.
Team ASTANA =37 hr 56.67 min
Team TOBLER=38 hr 5.47 min

Median- The median is the middle number when all values are put in order. For this example, there are 15 bikers. That means the median is the the average of the 7th and 8th place finisher.
Team ASTANA=38 hr
Team TOBLER=38 hr 9 min

Mode- The mode is the value that occurs most frequently. For this example, this means the results are the times that racers on each team finished most frequently.
Team ASTANA=37 hr 52 min and 38 hr
Team TOBLER=38 hr 9 min

Kurtosis- The kurtosis is the sharpness of a peak of a distribution curve. A number above one means the distribution has a peak, a number less than -1 means the distribution is relatively flat. A peak means that most of the values are close together. A flat distribution means the values are more spread out. For this example, both values are greater than one, this means that the distribution curve is peaked and the values are relatively close together.
Team ASTANA=1.168
Team TOBLER=2.927

Skewness (Population)- The skewness is a measurement of how symmetrical the distribution curve is. Positive numbers means the mean will be be to the left with a tail to the right. A negative number means the mean will be to the right with a tail to the left. Numbers above 1 or below -1 means there is a skew. The closer to 0, means the smaller the skew. For this example, team Astana has almost new skew whatsoever and team Tobler has a negative skew.
Team ASTANA=-0.00231
Team TOBLER=-1.0259

Standard Deviation- The standard deviation is a statistic that explains how tightly a group of values are to the mean. the picture below is the best way to explain it.
Team ASTANA=16.63
Team TOBLER=7.62

My job is to determine which team is better to invest in.

The individual race winner gets 75% of a $300,000 pool  ($225,000) and the owner gets 25% ($75,000)

The team that wins receives 65% of a $400,000 pool ($260,000) and the owner gets 35% ($140,000)

Based off of the last race in the TOUR de GEOGRAPHIA, there is a good chance that the first place finisher will come from Astana, which is a guaranteed $75,000. 

The prompt does not explain how the team wins. I am guessing that it is just an average of all of the racers to determine how well the team did communally. the statistic that would determine this is the mean. So based off of the mean, team Astana would also be the best team to invest in. 

PART II

Below is a map of Wisconsin. On the map are three points. The yellow star shows the geographic mean center of the state. This means the very middle of the state. The green dot shows where the mean center of population of the state was in 2010, and the red dot shows where the mean center of population was in 2015. These are points of where geographically the average person in Wisconsin lives. these points are influenced from every direction. If there are more people in the south, the dot will be further south. If there are more people living in the west, the dot will be further to the left. It can be noted that the dot from 2010 to 2015 has moved slightly west. A reason for this change must mean that there are more people living in the west. Perhaps a big city like Eau Claire has had a increase in population which moved the population mean center.