
Question 1
Incorrect

A novel antituberculosis medicine was compared to standard treatment and shown to cut the risk of death from 30 to 10 per 1000 people. How many patients would need to be treated (number need to treat (NNT)) in order to prevent ten additional tuberculosis deaths:
Your Answer: 50
Correct Answer: 500
Explanation:The risk of mortality in the control group (usual therapy) minus the risk of death in the treatment group equals the absolute risk reduction (ARR) of treatment.30/1000 minus 10/1000 = 20/1000 = 0.02NNT = 1/ARR = 1/0.02 = 50As a result, 50 people would need to be treated in order to prevent one additional fatality, and 500 people would need to be treated in order to avoid 10 additional deaths.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 2
Incorrect

Regarding relationships between two variables, what does a negative correlation coefficient indicate:
Your Answer: As one variable decreases, the other variable decreases
Correct Answer: The two variables are inversely related
Explanation:A negative correlation coefficient means that the two variables are inversely related e.g. socioeconomic class and mortality.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 3
Incorrect

Which of the following best describes the positive predictive value of a diagnostic test:
Your Answer: The proportion of patients with the disease who are correctly identified by the test as having the disease
Correct Answer: The proportion of individuals with a positive test result who have the disease
Explanation:Positive predictive value (PPV) is the proportion of individuals with a positive test result who actually have the disease.PPV = a/(a+b)

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 4
Correct

A new blood test is being developed to diagnose DVT. 1000 people presenting to ED with suspected DVT undergo the new blood test and the gold standard doppler ultrasound to confirm the diagnosis. Of the 1000 people, 77 are confirmed to have a DVT. Of the patients diagnosed with DVT, 75 test positive with the new diagnostic test and of the patients not diagnosed with DVT, 125 test positive with the new diagnostic test. What is the negative predictive value of this test:DVT YesDVT NoTotalPositive testa= 75b = 125200Negative testc = 2d = 798800Total779231000
Your Answer: 0.99
Explanation:Negative predictive value (NPV) is the proportion of individuals with a negative test result who do not have the disease.Negative predictive value (NPV) = d/(c+d) = 798/800 = 0.99 = 99%This means there is a 99% chance, if the test is negative, that the patient does not have a DVT.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 5
Correct

What does the correlation coefficient r = 0 indicate with regards to linear relationships between two variables?
Your Answer: There is no correlation between two variables
Explanation:r = 0 if there is no correlation between two variables. The closer that r is to 0, the weaker the correlation.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 6
Correct

Which of the following is an example of continuous data:
Your Answer: Height
Explanation:Continuous data is data where there is no limitation on the numerical value that the variable can take e.g. weight, height.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 7
Correct

Regarding likelihood ratios, which of the following statements is INCORRECT:
Your Answer: Likelihood ratios, like predictive values, are affected by the prevalence of the disease in the population.
Explanation:A likelihood ratio is a measure of the diagnostic value of a test. Likelihood ratios show how many times more likely patients with a disease are to have a particular test result than patients without the disease. Likelihood ratios are more useful than predictive values because they are calculated from sensitivity and specificity and therefore remain constant even when the prevalence of the disorder changes.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 8
Incorrect

The results from the study investigating the accuracy of a new diagnostic test can be displayed in the following format. How is the positive predictive value calculated:Those with diseaseThose without diseaseTotalTest positiveaba+bTest negativecdc+dTotala+cb+dn=a+b+c+d
Your Answer: a/(a+c)
Correct Answer: a/(a+b)
Explanation:Positive predictive value (PPV) is the proportion of individuals with a positive test result who actually have the disease.PPV = a/(a+b)

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 9
Correct

What is the interquartile range of the following data set: 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 70
Your Answer: 30
Explanation:5, 10, 15 /20, 25, 30 /35, 40, 45 /50, 60, 70Sample size (n) = 12Median = [(n+1)/2]th value = (12+1)/2 = 6.5 = halfway between 6th and 7th value = (30 +35)/2 = 32.5The lower (first) quartile = halfway between 15 and 20 = 17.5The upper (third) quartile = halfway between 45 and 50 = 47.5The interquartile range is the difference between the upper quartile and lower quartile = 47.5 – 17.5 = 30

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 10
Correct

A new chemotherapy drug is being tested. The intervention reduces the risk of death from 10 in 1000 to 5 in 1000. What is the number needed to treat to prevent one death:
Your Answer: 200
Explanation:Absolute risk reduction (ARR) of treatment = risk of death in control group – risk of death in treatment groupARR = (10/1000) – (5/1000) = 5/1000 = 0.005Number needed to treat (NNT) = 1/ARR = 1/0.005 = 200Therefore 200 people would need to be treated to prevent one extra death.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 11
Correct

If the null hypothesis is wrongly rejected when it is actually true, this is an example of:
Your Answer: A test with a type I error
Explanation:A type I error occurs when the null hypothesis is wrongly rejected when it is actually true and we conclude that there is a difference of effect when in reality there is none (a false positive result).

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 12
Incorrect

Question 13
Correct

Which of the following risk ratios indicates no difference in risk between two groups:
Your Answer: 1
Explanation:A risk ratio of 1 indicates no difference in risk between groups.If the risk ratio of an event is > 1, the rate of that event is increased in the exposed group compared to the control group.If the risk ratio is < 1, the rate of that event is reduced in the exposed group compared to the control group.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 14
Correct

A new blood test is being developed to diagnose DVT. 1000 people presenting to ED with suspected DVT undergo the new blood test and the gold standard doppler ultrasound to confirm the diagnosis. Of the 1000 people, 77 are confirmed to have a DVT. Of the patients diagnosed with DVT, 75 test positive with the new diagnostic test and of the patients not diagnosed with DVT, 125 test positive with the new diagnostic test. What is the positive predictive value of this test:DVT YesDVT NoTotalPositive testa= 75b = 125200Negative testc = 2d = 798800Total779231000
Your Answer: 0.375
Explanation:Positive predictive value (PPV) is the proportion of individuals with a positive test result who actually have the disease.Positive predictive value (PPV) = a/(a+b) = 75/200= 0.375 = 37.5%This means there is a 37.5% chance, if the test is positive, that the patient actually has a DVT.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 15
Incorrect

The results from the study investigating the accuracy of a new diagnostic test can be displayed in the following format. How is the negative predictive value calculated:Those with diseaseThose without diseaseTotalTest positiveaba+bTest negativecdc+dTotala+cb+dn=a+b+c+d
Your Answer: d/(b+d)
Correct Answer: d/(c+d)
Explanation:Negative predictive value (NPV) is the proportion of individuals with a negative test result who do not have the disease.NPV = d/(c+d)

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 16
Correct

The weight distribution in a group of patients included in a study was normal. The patients averaged 80 kg in weight. 5 kg was determined to be the standard deviation. Which of the following statements most accurately describes this group of patients:
Your Answer: 68% of the patients will weigh between 75 and 85 kg.
Explanation:We can estimate the range of values that would be anticipated to include particular proportions of observations if we know the mean and standard deviation of a collection of normally distributed data: 68.2 percent of the sample results fall within a one SD range above and below the mean (+/ 1 SD), implying that 68 percent of the patients will weigh between 75 and 85 kg. Because +/ 2 SD encompasses 95.4 percent of the data, around 95 percent of the patients will weigh between 70 and 90 kg. +/ 3 SD encompasses 99.7% of the values, implying that nearly all of the patients will weigh between 65 and 95 kg.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 17
Correct

A range of one standard deviation above and below the mean includes what approximate percentage of the sample values:
Your Answer: 0.68
Explanation:A range of one SD above and below the mean (+/ 1 SD) includes 68.2% of the sample values.A range of two SD above and below the mean (+/ 2 SD) includes 95.4% of the sample values.A range of three SD above and below the mean (+/ 3 SD) includes 99.7% of the sample values.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 18
Incorrect

A type II error occurs when:
Your Answer: The alternative hypothesis is rejected when it is true.
Correct Answer: The null hypothesis is accepted when it is false.
Explanation:A type II error occurs when the null hypothesis is wrongly accepted when it is actually false and we conclude that there is no evidence of a difference in effect when one really exists (a false negative result).

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 19
Correct

A new test is being developed to diagnose chlamydia. 1000 people aged 15 – 35 years attending a GUM clinic undergo the new test and the current gold standard nucleic acid amplification test (NAAT) to confirm the diagnosis. Of the 1000 people, 250 are diagnosed with chlamydia. Of the patients diagnosed with chlamydia, 240 test positive with the new diagnostic test and of the patients not diagnosed with chlamydia, 150 test positive with the new diagnostic test. What is the negative predictive value of this test:Chlamydia YesChlamydia NoTotalPositive testa= 240b = 150390Negative testc = 10d = 600610Total2507501000
Your Answer: 0.98
Explanation:Negative predictive value (NPV) is the proportion of individuals with a negative test result who do not have the disease.Negative predictive value (NPV) = d/(c+d) = 600/610 = 0.98 = 98%This means there is a 98% chance, if the test is negative, that the patient does not have chlamydia.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 20
Correct

Regarding linear relationships between two variables, what does a positive correlation coefficient indicate:
Your Answer: The two variables are directly proportional
Explanation:A positive correlation coefficient means that the two variables are directly proportional e.g. height and weight in healthy growing children.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 21
Correct

A new test is being developed to diagnose chlamydia. 1000 people aged 15 – 35 years attending a GUM clinic undergo the new test and the current gold standard nucleic acid amplification test (NAAT) to confirm the diagnosis. Of the 1000 people, 250 are diagnosed with chlamydia. Of the patients diagnosed with chlamydia, 240 test positive with the new diagnostic test and of the patients not diagnosed with chlamydia, 150 test positive with the new diagnostic test. What is the positive predictive value of this test:Chlamydia YesChlamydia NoTotalPositive testa= 240b = 150390Negative testc = 10d = 600610Total2507501000
Your Answer: 0.62
Explanation:Positive predictive value (PPV) is the proportion of individuals with a positive test result who actually have the disease.Positive predictive value (PPV) = a/(a+b) = 240/390 = 0.62 = 62%This means there is a 62% chance, if the test is positive, that the patient actually has chlamydia.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 22
Incorrect

What is the interquartile range for these numbers: 11, 4, 6, 8, 3, 10, 8, 10, 4, 12, 31?
Your Answer: 8
Correct Answer: 7
Explanation:We obtain 3, 4, 4, 6, 8, 8, 10, 11, 12, and 31, and sample size (n) = 11 when we order the data. [(n+1)/2] = median 6th value = (11+1)/2 = [(n+1)/4] represents the bottom (first) quartile. (3rd value = 4th value = (11 + 1)/4 3[(n+1)/4] for the top (third) quartile 3[(11 + 1)/4] = 9th value = 11th value = 11th value = 11th value = 11th value = 11th value = 11th value = 11th value = 11th The difference between the upper and lower quartiles is the interquartile range, which is equal to 11 minus 4 = 7.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 23
Incorrect

A p value < 0.05 obtained from a study with a significance level (α) of 0.05, means all of the following, EXCEPT:
Your Answer: the probability of obtaining the result by chance is less than 1 in 20.
Correct Answer: the result is clinically significant.
Explanation:A p value < 0.05:is statistically significantmeans that the probability of obtaining a given result by chance is less than 1 in 20means the null hypothesis is rejectedmeans there is evidence of an association between a variable and an outcomeNote that this does not tell us whether the result is clinically significant.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 24
Correct

Which of the following data types does a painscoring system represent?
Your Answer: Ordinal
Explanation:Pain scoring systems are processes for assessing pain and the severity of illnesses that have been scientifically designed and tested. An example of ordinal categorical data is a pain scoring system.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 25
Correct

Which of the following is an example of discrete data:
Your Answer: Number of children
Explanation:Discrete data is quantitative data that can only take whole numerical values e.g. number of children, number of days missed from work.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 26
Correct

Regarding probability distribution, which of the following statements is CORRECT:
Your Answer: In a negative skew, the mass of distribution is concentrated on the right.
Explanation:Distribution of data is usually unimodal (one peak) but may be bimodal (two peaks) or uniform (no peaks, each value equally likely). The normal distribution is a symmetrical bellshaped curve. The mean, median, and mode of a normal distribution are equal. In a positive skew, the right tail is longer and the mass of distribution is concentrated on the left; mean > median > mode. In a negative skew, the left tail is longer and the mass of distribution is concentrated on the right; mean < median < mode.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 27
Correct

Which of these is an example of ordinal data?
Your Answer: Disease staging system
Explanation:Categorical data or data that is ordered is Ordinal data e.g. disease staging system, pain scoring system.Disease staging system is the correct answer

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 28
Correct

Which of the following terms describes the proportion of individuals with a negative test result who actually do not have a disease:
Your Answer: Negative predictive value
Explanation:Negative predictive value (NPV) is the proportion of individuals with a negative test result who do not have the disease.NPV = d/(c+d)

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 29
Correct

The interquartile range (IQ) is often displayed using which of the following:
Your Answer: Box and whisker plot
Explanation:A boxplot is a vertical or horizontal rectangle used to display the interquartile range, with the ends of the rectangle corresponding to the upper and lower quartiles of the data values. The box contains 50% of the data values. A line drawn through the rectangle corresponds to the median value. Whiskers, starting at the ends of the rectangle usually indicate the minimum and maximum values, therefore the entire box and whisker plot represents the range. Any outliers can be plotted independent of the box and whisker plot.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics


Question 30
Incorrect

Regarding the power of a study, which of the following statements is INCORRECT:
Your Answer: The power of a study increases with sample size.
Correct Answer: The power of a study is not affected by data variability.
Explanation:A study should only be undertaken if the power is at least 80%; a study power set at 80% accepts a likelihood of 1 in 5 (20%) of missing a statistically significant difference where one exists.The determinants of power are:the sample size (the power increases with sample size)the variability of the observations (the power increases as the variability decreases)the effect size of interest (the power is greater for a larger expected effect size)and the significance level, α (the power is greater if the significance level is larger); therefore the probability of a type I error increases as the probability of a type II error decreases.

This question is part of the following fields:
 Evidence Based Medicine
 Statistics

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