STATISTICS/MCQ:
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.
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
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
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. You
are designing a study to investigate whether ethnicity is associated with
hypertension. You have a cohort of 500 patients of Asian, African , Indian,
American 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
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.
Q.
Which of the following best describes a type I error?
A. There is a positive result on a screening test, but the patient does not
have the disease.
B. There is a positive result on a screening test, and the patient does have
the disease.
C. There is a negative result on a screening test,
and the patient does not have the disease.
D. There is a negative result on a screening test,
but the patient does have the disease.
E. None of the above
Ans: E.
Type I error is
that of having a false-positive result. So type I error equals the number of
false-positive results over the total number of patients with true results that
are negative or not diseased. Type II error is the false-negative mistake.
Thus, type II error equals the number of false negatives over the total number of
patients with disease, or with true results that are positive
