The assumptions to check for confidence intervals are the same as it is for hypothesis tests.

True

False

Choose all that apply. The significance level is

A)

B) The probability of a type II error

C) the confidence level

D) the probability of a type I error

E) chosen by the researchers

If we fail to reject the null, but the null is actually false, we've

1. Proved what we wanted to prove
2. Made a type I error
3. Found evidence that supports the alternative
4. Made a type II error

We're trying to show that the true average resting pulse rate of teenagers is greater than 70 . beats per minute. What would our parameter be?

2. P

We're trying to show that the true proportion of fractures that are compound is less than 20%. What would our alternative hypothesis be?

1. P < 0.2
2. P0.20.2
3. P > 0.2
4. <0.2

We're trying to show that the true average length of an adult male femur is greater than 1.5 feet. What would a type I error mean?

1. Our test results provide evidence that the true average is greater than 1.5, but it's actually less
2. Our test results provide evidence that it's less than 1.5 feet, but it's actually greater
3. Our tests results supported that the average length is greater than 1.5 feet
4. Our test results supported that the average length is less than 1.5 feet

We're trying to show that the true proportion of Americans that are obese is greater than 40%. What would our parameter be?

1. P

We're trying to show that the true proportion of blood donations that are O+ is different than 50%. What would our alternative hypothesis be?

1. P0.5
2. 0.50.5
3. P > 0.5
4. P < 0.5

We're trying to show that the true average length of a hospital stay for a CoVid patient is less than 20 days. What would our parameter be?

2. P