Running Statistics
Rachel Passman, Ciara Gilligan, and Ryan Biemuller
• Man started running out of necessity and was used for
communication
– Pheidippides was a messenger who brought news of battle
• First sign of running as recreation
– 3200m race at the Olympics in Egypt (3000 B.C)
• 17th century, running was used for gambling purposes
• Training for running began with Finn Paavo Nurmi and coach
Pikala
– Saw relationship between work and rest and understood
importance of interval training
– Training became known as the terrace training
• 18th Century
– Light weight leather shoe that can
grip the ground
• 19th Century
– Croquet shoe with a rubber sole
with a canvas upper with laces
– Spiked leather shoes also invented
• 20th Century
– Created leather strip around shoe
to reduce stretching (known today
as Keds)
– Converse sneakers
• 21st Century
– modern synthetic shoes are made
of lightweight mesh fabric uppers
and lightweight synthetic soles
– chosen for maximum flexibility
and comfort
• The proportion of runners who wear
legitimate running apparel
• What running sneaker is most
popular
• What running sneaker is most
popular within gender
• We went to go certain locations and parks such as
Meyer Way Park, Turk Park, IPW, and Kemper Park
– Supposed to go to stores
• Tried to go to parks at two different times
– Early Saturday morning
– After school Monday
• We observed data of runners coming through the
parks
– Type of sneaker
– Type of sneaker vs. gender
– Running apparel
Ho: The observed frequency distribution of type of running shoe fits the
expected distribution.
Ha: The observed frequency distribution of type of running shoe doesn’t
fit the expected distribution.
Assumptions:
1. SRS
2. All expected counts are greater than or equal to 5
x
2
=∑
2
(obs-exp) / exp
= 24.00
P(x^2>24I df=6)= 0.00052
1. assumed
2. check
We reject Ho because our p-value is less than
alpha which equals 0.05.
We have sufficient evidence that the observed
frequency distribution of the type of running
shoe doesn’t fit the expected distribution.
Ho: There is no association between the type of running shoe and gender
variables.
Ha: There is an association between the type of running shoe and gender
variables.
Assumptions:
1. 2 independent SRS
2. All expected counts are greater than or equal to 5
x
2
2
=∑
(obs-exp) / exp = 3. 741
P(x^2>3.741I df=6)= 0.71
1. assumed
2. no, but cont.
We fail to reject Ho because our p-value is
greater than alpha which equals 0.05.
We have sufficient evidence that there is no
association between the type of running shoe
and gender variables
Legit, 18
Not, 35
Ho: p=0.50
Ha: p<0.50
Assumptions:
1.
2.
3.
SRS
Np
n(1-p) >10
Pop > 10n
^
Z= p-p/
1. assumed
2. (53x 0.50)
(53x0.50)
3. pop> 10x53
=-2.335
P(z<-2.335)= 0.02
> 10 (no, but cont.)
We reject Ho because our p-value is less than
alpha which equals 0.05.
We have sufficient evidence that the proportion
of people who wear legitimate apparel while
running is < 0.50.
• The most popular
brand of shoe is not
affected by gender
• Most popular and least
popular stay constant
within both genders
• More than 50% of
runners do not wear
legitimate apparel
(wear shorts and tees)
• Only analyzed runners in immediate area
– Only observed runners in Bucks County
• Only went to parks
– Runners might not have been as legitimate as
runners shopping in the stores
• Didn’t include people running at home or at
gym
– Didn’t ask questions
• If we were allowed to be in stores, we
believed our legitimate apparel would have
changed.
– The shoe brands, such as Soucony and Brooks
would be more popular
• We believed prior to the test that Nike would
be most popular and gender would have no
affect on type of shoe.