Answer: 5% of the sample results will be unusually high or unusually low compared to the true population value, just by chance.
What is the most common level of confidence used to construct confidence intervals?
5%
90%
95%
100%
Answer: c
Which of the following is a correct interpretation of a 90% confidence interval?
90% of the random samples you could select would result in intervals that contain the true population value.
90% of the population values should be close to our sample results.
Once a specific sample has been selected, the probability that its resulting confidence interval contains the true population value is 90%.
All of the above statements are true.
Answer: a
Which of the following statements is false?
Confidence intervals are always close to their true population values.
Confidence intervals vary from one sample to the next.
The key to constructing confidence intervals is to understand what kind of dissimilarity we should expect to see in various samples from the same population.
None of the above statements are false.
Answer: a
How does a 90% confidence interval compare to a 95% confidence interval?
Fewer of the samples will result in intervals that contain the true population value in the 90% case.
Fewer of the samples will result in incorrect intervals in the 90% case.
With the 90% confidence interval you are less willing to take a chance on missing the true value.
All of the above.
Answer: a
A(n) _______________ is an interval of values computed from the sample data that is almost sure to cover the true population number.
