Answer:
Step-by-step explanation:
Hello!
The objective is to study whether there is a greater force after impacting on one- handed backhand drive in advanced tennis players than in intermediate tennis players.
Sample 1: Advanced tennis players
X₁: Force (N) on the hand just after impact on a one- handed backhand drive for an advanced tennis player.
n₁= 6
X[bar]₁= 40.29 N
S₁= 11.29
Sample 2: Intermediate players
X₂: Force (N) on the hand just after impact on a one- handed backhand drive for an intermediate tennis player.
n₂= 8
X[bar]₂= 21.40
S₂= 8.30
Assuming that both variables have a normal distribution and both population variances are equal, to compare these two populations is best to do so trough their population means using a t-test for independent samples.
If the force is greater for the advanced players than for the intermediate players, then you'd expect the population mean for the advanced players to be greater than the population mean for the intermediate players:
H₀: μ₁ ≤ μ₂
H₁: μ₁ > μ₂
α: 0.05
[tex]t= \frac{(X_[bar]_1-X[bar]_2)-(Mu_1-Mu_2)}{Sa\sqrt{\frac{1}{n_1} +\frac{1}{n_2} } } ~~t_{n_1+n_2-2}[/tex]
[tex]Sa= \sqrt{\frac{(n_1-1)S_1^2+(n_2-1)S_2^2}{n_1+n_2-2} } = \sqrt{\frac{5*127.51+7*68.92}{6+8-2} }= 9.66[/tex]
[tex]t_{H_0}= \frac{(40.29-21.40)-0}{9.66\sqrt{\frac{1}{6} +\frac{1}{8} } } = 3.62[/tex]
Using the p-value approach, the decision rule is
If p-value ≤ α, reject the null hypothesis
If p-value > α, do not reject the null hypothesis
The p-value for this test is 0.00024, it is less than the level of significance, so the decision is to reject the null hypothesis.
This means that at a 5% significance level you can conclude that the average force experienced on the hand after a one-handed backhand drive for advanced players is greater than the average force experienced on the hand after a one-handed backhand drive for intermediate players.
I hope this helps!
