In: Statistics and Probability
ANSWER-
Here we have to test
1).Hypothesis for mean-
H0: mean of method A and B are statistically same.
V/s
H1:mean of method A and B are statistically not same.
2).Hypothesis for variance.
H0:variance of method A and B are statistically same.
V/s
H1:variance of method A and B are statistically not same.
# R-code.
x=c(19,10.3,20.6,10,14.4,11.5,17.1,21.9,20.5,14.7,16.9,21.4);x
y=c(9.7,10.9,18.6,13.7,11.7,10.6,10.3,17.7,19.9,20.9,15.3,19);y
a=t.test(x,y);a
b=var.test(x,y);b
# output -
[1] 19.0 10.3 20.6 10.0 14.4 11.5 17.1 21.9 20.5 14.7 16.9 21.4 [1] 9.7 10.9 18.6 13.7 11.7 10.6 10.3 17.7 19.9 20.9 15.3 19.0 Welch Two Sample t-test data: x and y t = 0.95751, df = 21.979, p-value = 0.3487 alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: -1.943370 5.276704 sample estimates: mean of x mean of y 16.52500 14.85833 here p-value is greater than 0.05 thus we accept H0 and conclude that mean for method A and B are same. F test to compare two variances data: x and y F = 1.0631, num df = 11, denom df = 11, p-value = 0.921 alternative hypothesis: true ratio of variances is not equal to 1 95 percent confidence interval: 0.3060448 3.6929155 sample estimates: ratio of variances
1.063107
here p-value is greater than 0.05 thus we accept H0 and conclude that variance for method A and B are same.
Thus final answer is Option
B) neither means nor variances are statistically different.