In: Statistics and Probability
To determine if chocolate milk was as effective as other
carbohydrate replacement drinks, nine male cyclists performed an
intense workout followed by a drink and a rest period. At the end
of the rest period, each cyclist performed an endurance trial where
he exercised until exhausted and time to exhaustion was measured.
Each cyclist completed the entire regimen on two different days. On
one day the drink provided was chocolate milk and on the other day
the drink provided was a carbohydrate replacement drink.
Data consistent with summary quantities appear in the table below.
(Use a statistical computer package to calculate the
P-value. Subtract the carbohydrate replacement times from
the chocolate milk times. Round your test statistic to two decimal
places, your df down to the nearest whole number, and the
P-value to three decimal places.)
Cyclist | Time to Exhaustion (minutes) | ||||||||
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | |
Chocolate Milk |
36.91 | 58.23 | 26.58 | 37.07 | 31.79 | 47.98 | 45.50 | 34.85 | 30.21 |
Carbohydrate Replacement |
47.12 | 7.03 | 15.59 | 16.65 | 24.14 | 27.57 | 41.14 | 11.70 | 32.83 |
t | = |
df | = |
P | = |
Is there sufficient evidence to suggest that the mean time to
exhaustion is greater after chocolate milk than after carbohydrate
replacement drink? Use a significance level of 0.05.
Yes
No
Solution:
Suppose,
Sample 1 = chocolate milk
and sample 2 = carbohydrate replacement drink
hence , n1 = n2 = sample size = 9
Sample mean = = 38.79 and = 24.86
Standard deviation = s1 = 10.01 and s2 = 13.58
There not sufficient evidence to suggest that the mean time to exhaustion is greater after chocolate milk than after carbohydrate replacement drink.
Done