In: Statistics and Probability
Please ANSWER IN R CODE.
Problem:
Vital capacity is a measure of the amount of air that someone can exhale after taking a deep breath, Data was collected on brass players and a control group.
Brass Player | Control Group |
4.7 | 4.2 |
4.6 | 4.7 |
4.3 | 5.1 |
4.5 | 4.7 |
5.5 | 5.0 |
4.9 | |
5.3 |
Please provide all relevant work. That is your commands, the output and any interpretations/conclusions that are necessary.
The R output is:
The R code is:
Brass <- c(4.7,4.6,4.3,4.5,5.5,4.9,5.3)
Control <- c(4.2,4.7,5.1,4.7,5)
t.test(Brass, Control, alternative= "greater", conf.level =
0.95)
t.test(Brass, Control, alternative= "greater", conf.level = 0.95,
var.equal = TRUE)
The hypothesis being tested is:
H0: µ1 = µ2
H1: µ1 > µ2
The p-value is 0.3525.
Since the p-value (0.3525) is greater than the significance level (0.05), we cannot reject the null hypothesis.
Therefore, we cannot conclude that the population mean for brass is larger than that for control.
The 95% confidence interval for the difference of two population means is between -0.3241937 and 0.
The hypothesis being tested is:
H0: µ1 = µ2
H1: µ1 > µ2
The p-value is 0.3577.
Since the p-value (0.3577) is greater than the significance level (0.05), we cannot reject the null hypothesis.
Therefore, we cannot conclude that the population mean for brass is larger than that for control.
The 95% confidence interval for the difference of two population means is between -0.3394088 and 0.
Please give me a thumbs-up if this helps you out. Thank you!