If your \(x = 542\) (ie the number of “successes” and your \(n = 3611\), this is how you can have R calculate a 90% Confidence Interval for you.

binom.test(x = 542, n = 3611,  conf.level = .90)[["conf.int"]]
## [1] 0.1403939 0.1602214
## attr(,"conf.level")
## [1] 0.9

25.

  1. Point estimate = 0.181

  2. 341.8 ??? 10; less than 5% of the population is included in the sample

  3. lower bound = .1678 ; upper bound = .1942

  4. 90% confidence that the range for people who donated blood ranges between .168 and .194

26.

  1. Point estimate = .43

  2. 282 ??? 10; less than 5% of the population is included in the sample

  3. lower bound: .4; upper bound: .46

  4. 95% confidence lies between the range .4 and .46

27.

  1. Point estimate= .52

  2. 250.34 ??? 10; less than 5% of the population is included in the sample.

  3. lower bound: .489; upper bound: .551

  4. no, since it is outside the confidence interval

  5. 95% confidence range lies between .450 and .512

28.

  1. Point estimate= .75

  2. 192 ??? 10; less than 5% of the population is included in the sample.

  3. lower bound: .72; upper bound .78

  4. no since the range is between .72 and .78

  5. 99% confidence suggests that range lies between .28 and .22

29.

  1. 95% confidence interval lies between .07 and 1.5

  2. 99% confidence interval lies between .6 and .16

  3. the margin for error increases as the level of confidence increases since margin for error for 95% was +-.04, for 99% was +- .05