Random samples were collected from two populations. The assumptions were checked and a 94% confidence interval for the difference of two means was constructed using this code. t.test( x1 , y1 , var.equal = FALSE , conf.level = .94 ) As you can see, there was no reason(or there was doubt) to believe that the unknown variances were equal. The results are given below. (We are assuming that this is all appropriate.) What is the upper bound on this confidence interval? Two Sample t-test data:  x1 and y1 t = 1.572, df = 125, p-value = 0.049 alternative hypothesis: true difference in means is not equal to 0 94 percent confidence interval:  -2.038  2.220 sample estimates: mean of x mean of y  6.585 8.247  (This question is meant to test you on your ability to find values in an R output. Many of the values given here are randomly generated and may be inconsistent with each other. Do not worry about that, this is just asking you to find a number in the output. Unless a specific warning like this is give, you should assume that the R output has not been modified. )  Short answer