STATISTICS /PGQUESTIONS
Q. A
screening test is performed and there are 10 positive results. Of these, six
are false positives. Of note, there are exactly 10 people with disease in the
population screened. Which of the following is true?
A. This
test has a 40% sensitivity.
B. This
test has a 60% sensitivity.
C. This
test has a 100% sensitivity.
D. This
test has a 60% specificity.
E. This
test has a 40% specificity.
Ans:. A.
We know that there are
six false positives. Thus, the remaining four positive tests must be true
positives. Since there are exactly 10 people with disease, there must be six
false negatives. Using this information we can calculate the sensitivity, but
not the specificity. Sensitivity is a/(a + c)= 4/10 =0.4,
or 40%.
Q. A
screening test for diabetes is being evaluated. You know that 900 nondiabetics
and 100 diabetics are being screened. There are 100 positive tests and of
these, 90 have diabetes.
Which
of the following is true in this population?
A. The
NPV of the test is 0.9.
B. The
NPV of the test is 0.5.
C. The
PNV of the test is 0.1.
D. The
PPV of the test is 0.1.
E. The
PPV of the test is 0.9.
Ans: E.
Ninety of the
100 positive screens have diabetes, so they must be true positives. The
remaining
10 must be false
positives. Since there are 100 people with diabetes, there must be 10 false
negatives as well. So we can calculate PPV but not NPV. The PPV is equal to
90/100 = 0.9.
Q. Given the following collection
of data {1,2,4,6,7,8,9}, which is correct?
A. The mean is 5.0.
B. The median is 5.0.
C. The median is 5.5.
D. The median is 6.0.
E. The mean is 6.0.
A. The mean is 5.0.
B. The median is 5.0.
C. The median is 5.5.
D. The median is 6.0.
E. The mean is 6.0.
Ans:. D.
Given the set of
numbers {1,2,4,6,7,8,9}, the sum of these numbers is 37 and there are seven
values, so the mean is 37/7 =5and2/7, or 5.28. The median, which is the center
of an odd number of values, is the number 6, with 1, 2, and 4 below and 7, 8,
and 9 above.
Q. Given
the following collection of data {1,1,1,1,2,3,5,5, 6,6,7,7,9,9}, which of the
following is correct?
A. The mode is 1.
B. The mean is 4.5.
C. The median is 6.
D. A and B are correct.
E. A and C are correct
A. The mode is 1.
B. The mean is 4.5.
C. The median is 6.
D. A and B are correct.
E. A and C are correct
Ans. D.
Given the set of
numbers {1,1,1,1,2,3,5,5,6,6,7,7,9,9}, there are 14 numbers, and their sum is
63. Thus the mean is 4.5; clearly, the median is 5; and the mode is 1. Thus,
the answer is (D), which is a mode of 1 and a mean of 4.5.
Q. You
are told that your patient has a cholesterol result that is the mean of that in
the population. Which of the following distributions would also mean that his
result is necessarily
greater than half of the population?
A. Skewed to the left
B. Skewed to the right
C. Uniform
D. Normal
E. Bimodal
greater than half of the population?
A. Skewed to the left
B. Skewed to the right
C. Uniform
D. Normal
E. Bimodal
Ans: B.
The question
asks, “In what type of distribution is the mean greater than the median?”The
mean will equal the median in normal and uniform distributions. In a symmetric
bimodal distribution this will also be true. In a skewed-to-the-left
distribution, the median will be greater than the mean, whereas in a
skewed-tothe- right distribution, the mean will be greater than the median
Q. Which
of the following statements is true about a 95% confidence interval?
A. There is a 95% chance that the true value is in the interval.
B. Ninety-five percent of the time, the true value will fall in the interval.
C. If you repeated the study 20 times, the true value would be in the interval at least once.
D. If the interval does not contain the null hypothesis, you can be 95% certain that your result is the true value.
E. If you repeat the study an infinite number of times, the results would fall in the interval 95% of the time
A. There is a 95% chance that the true value is in the interval.
B. Ninety-five percent of the time, the true value will fall in the interval.
C. If you repeated the study 20 times, the true value would be in the interval at least once.
D. If the interval does not contain the null hypothesis, you can be 95% certain that your result is the true value.
E. If you repeat the study an infinite number of times, the results would fall in the interval 95% of the time
Ans;E.
What a 95% CI
tells you is that if you repeated the same experiment that you did to get your
summary statistic (e.g., the mean or proportion), an infinite number of times,
95% of the time you would get a value that falls within the 95% CI. It
does not tell you that the true value you are seeking is going to fall
within your CI, particularly because your experiment may be faulty
or biased; thus, the true value may be missed by the CI. Even with a
perfectly performed experiment, the CI is not used to tell you about the
true value; it gives just the results of that
particular
experiment.
Q. You are
designing a study to investigate whether ethnicity is associated with type II
DM. You have a cohort of 1000 patients of Asian, African American, Caucasian,
and Latino ethnicity. Which of the following tests would be the best to compare
the results of the study?
A. Student t test
B. Power analysis
C. z test
D. Chi-square test
E. Bonferroni correction
A. Student t test
B. Power analysis
C. z test
D. Chi-square test
E. Bonferroni correction
Ans. D.
In this study
design, you are attempting to determine whether there is a difference in any of
these groups of patients with respect to the risk for type 2 diabetes. The test
that is needed must be able to compare proportions between multiple groups. The
only one that can do that is the chi-square test. The student t test is
to compare two means; the z test is to compare the proportions of two
groups. A power analysis is performed to measure the power of a particular
study to reject the null hypothesis. A Bonferroni correction is performed when
making more than one comparison, using, for example, a student t test. Using
a cutoff of the test that allows a 5% chance of type I error goes awry when you
make many comparisons of outcomes in the same study. For example, if you
compared 100 different means, on average you would expect five of them to meet
the p _ .05 requirement. Thus, a Bonferroni or, more commonly, the
student- Newman-Keuls test can be used to adjust the cutoff when making multiple
comparisons.
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