Biostatistics — MCQs

A study was conducted to evaluate the effectiveness of a new antidiabetic drug. The fasting blood glucose levels (mg/dL) of 5 diabetic patients after 3 months of treatment were: 110, 94, 102, 98, 96. Consider the following statements about this data: 1. The range of blood glucose levels is 16 mg/dL 2. The median blood glucose level is 98 mg/dL 3. The standard deviation is √10 mg/dL

Q766

What is the Standardized Mortality Ratio (SMR) for the hazardous industry workers (as compared to national population)?

Q767

Consider the following: 1. Standard deviation 2. Range 3. Mode 4. Median Among the above, which is/are the measure/measures of dispersion?

Q768

In a normal curve, the area between one standard deviation on either side of the mean will include:

Q769

The relationship between birth rate and maternal hemoglobin is best studied by:

Q770

Which of the following statements is true about direct age standardization?

Biostatistics Indian Medical PG Practice Questions and MCQs

Question 761: The agreement (yes/no) between two observers is statistically measured by:

A. Correlation coefficient
B. Sensitivity
C. Kappa coefficient (Correct Answer)
D. Specificity

Explanation: **Kappa coefficient** - The **kappa coefficient** measures the **inter-rater agreement** for qualitative items, such as a "yes/no" decision, beyond what would be expected by chance. - It takes into account the observed agreement and the agreement expected by chance, providing a more robust measure of agreement than simple percentage agreement. *Correlation coefficient* - The **correlation coefficient** measures the **strength and direction of a linear relationship between two quantitative variables**, not the agreement between two observers on a categorical outcome. - It is used for continuous data and indicates how closely data points fit a linear regression line. *Sensitivity* - **Sensitivity** is a measure of a test's ability to correctly identify individuals who **have a disease (true positive rate)**. - It is not used to assess the agreement between two observers but rather the performance of a diagnostic test against a gold standard. *Specificity* - **Specificity** is a measure of a test's ability to correctly identify individuals who **do not have a disease (true negative rate)**. - Like sensitivity, it evaluates the performance of a diagnostic test and not the consistency of observations between two different raters.

Question 762: The villages A and B have the following age compositions: Which of the following is the best indicator for comparing the death rates of these two villages?

A. Crude death rate
B. Specific death rate
C. Proportional mortality rate
D. Age standardized death rate (Correct Answer)

Explanation: ***Age standardized death rate*** - This method adjusts for differences in the **age structures** of the two populations, providing a more accurate comparison of underlying mortality risks. - Since the question clearly shows significant differences in the age compositions of Village A and Village B, age standardization is essential to avoid misleading conclusions drawn from crude rates. *Crude death rate* - The crude death rate is the total number of deaths in a period divided by the total population, which **does not account for age differences**. - Comparing crude death rates between populations with different age structures can be misleading because older populations naturally have higher death rates. *Specific death rate* - Specific death rates refer to death rates for particular **age groups, causes, or other characteristics**. - While useful for detailed analysis, it doesn't provide a single, summary measure for comparing the overall mortality burden between two populations with differing age structures. *Proportional mortality rate* - This rate indicates the **proportion of deaths due to a specific cause** out of all deaths. - It does not measure the risk of dying in a population and is not suitable for comparing overall mortality burden between two communities, especially when age structures vary significantly.

Question 763: What is the sensitivity of EEG for detecting brain tumours as per the information given below?

A. 90% (Correct Answer)
B. 99.99%
C. 0.07%
D. 85%

Explanation: ***90%*** - Sensitivity is calculated as **True Positives / (True Positives + False Negatives)**. - Based on the table provided, among patients with brain tumors (disease positive), 36 cases were correctly identified by EEG and 4 cases were missed. - Sensitivity = 36/(36+4) = 36/40 = 0.9 or **90%**. - This indicates that the EEG test correctly identifies 90% of patients who actually have brain tumors. - High sensitivity is important for screening tests to minimize false negatives. *99.99%* - This extremely high percentage is incorrect and not supported by the data. - It would indicate near-perfect detection of all brain tumor cases, which contradicts the table showing 4 missed cases out of 40. - Results from miscalculation or misinterpretation of the sensitivity formula. *0.07%* - This extremely low value represents a fundamental calculation error. - Such low sensitivity would indicate the test is essentially useless for detecting brain tumors. - Does not correspond to any reasonable interpretation of the given data. *85%* - While close to the correct answer, this is mathematically incorrect. - Likely results from calculation error or rounding mistakes. - The correct calculation (36/40) yields exactly 90%, not 85%.

Question 764: Which one of the following statements regarding predictive value of a positive test is true?

A. It does not tell about diagnostic power of test
B. The more prevalent the disease, the less accurate the test is
C. It tells the probability that a patient with positive test does not have the disease in question
D. It tells the probability that a patient with positive test has the disease in question (Correct Answer)

Explanation: ***It tells the probability that a patient with positive test has the disease in question*** - The **positive predictive value (PPV)** is the probability that an individual with a **positive test result** actually has the disease. - It helps clinicians understand the likelihood of a true positive diagnosis in a given population. *It does not tell about diagnostic power of test* - While PPV is influenced by disease prevalence, it is a crucial measure of a test's **diagnostic utility** in a clinical setting. - It helps in interpreting the meaning of a positive result for an individual patient. *The more prevalent the disease, the less accurate the test is* - This statement is incorrect; the **higher the prevalence**, the **higher the positive predictive value** (PPV) of a test, assuming sensitivity and specificity remain constant. - Test accuracy (sensitivity and specificity) is independent of disease prevalence. *It tells the probability that a patient with positive test does not have the disease in question* - This describes the **false positive rate** or **1 - positive predictive value (PPV)**, not the PPV itself. - The PPV specifically refers to the probability of having the disease given a positive result.

Question 765: A study was conducted to evaluate the effectiveness of a new antidiabetic drug. The fasting blood glucose levels (mg/dL) of 5 diabetic patients after 3 months of treatment were: 110, 94, 102, 98, 96. Consider the following statements about this data: 1. The range of blood glucose levels is 16 mg/dL 2. The median blood glucose level is 98 mg/dL 3. The standard deviation is √10 mg/dL

A. 1, 2 and 3
B. 1 and 3 only
C. 1 and 2 only (Correct Answer)
D. 2 and 3 only

Explanation: ***1 and 2 only*** - **Statement 1 is correct**: The **range** is calculated as maximum value minus minimum value. Ordering the data: 94, 96, 98, 102, 110 mg/dL. Range = 110 - 94 = **16 mg/dL** ✓ - **Statement 2 is correct**: For the ordered dataset (94, 96, 98, 102, 110), with n=5 observations, the **median** is the middle (3rd) value = **98 mg/dL** ✓ - **Statement 3 is incorrect**: To calculate standard deviation: - Mean (x̄) = (110 + 94 + 102 + 98 + 96) / 5 = **100 mg/dL** - Deviations from mean: 10, -6, 2, -2, -4 - Sum of squared deviations: 100 + 36 + 4 + 4 + 16 = **160** - Sample variance = 160 / (n-1) = 160 / 4 = **40** - Standard deviation = √40 = **2√10 ≈ 6.32 mg/dL** (NOT √10 ≈ 3.16 mg/dL) ✗ *1, 2 and 3* - This would only be correct if all three statements were true. However, **statement 3 is incorrect** as the actual standard deviation is √40 (or 2√10), not √10. *1 and 3 only* - This is incorrect because **statement 3 is false** (SD = √40, not √10), while statement 2 is actually correct. *2 and 3 only* - This is incorrect because **statement 1 is correct** (range is indeed 16 mg/dL) and **statement 3 is incorrect** (SD ≠ √10).

Question 766: What is the Standardized Mortality Ratio (SMR) for the hazardous industry workers (as compared to national population)?

A. 110
B. 100
C. 120 (Correct Answer)
D. 130

Explanation: ***120*** - To calculate the Standardized Mortality Ratio (SMR), we first need to calculate the **expected deaths** for the hazardous industry workers based on the national death rates. - The formula for expected deaths in each age group is: (National death rate / 1000) × Number of hazardous industry workers - For age group 25-34: Expected deaths = (2.0 / 1000) × 3000 = **6** - For age group 35-44: Expected deaths = (3.5 / 1000) × 2000 = **7** - For age group 45-54: Expected deaths = (6.0 / 1000) × 2000 = **12** - **Total expected deaths** = 6 + 7 + 12 = **25** - **Total observed deaths** = 8 + 9 + 13 = **30** - **SMR formula**: (Total Observed Deaths / Total Expected Deaths) × 100 - **SMR = (30 / 25) × 100 = 1.2 × 100 = 120** - This indicates that the hazardous industry workers have a **20% higher mortality rate** compared to the national population after age-standardization. *100* - An SMR of 100 would indicate that the observed mortality equals the expected mortality (no difference from the national average). - However, the observed deaths (30) exceed the expected deaths (25), so the SMR must be greater than 100. - This option represents the null value where there is no excess mortality. *110* - This option underestimates the actual SMR calculated from the data. - An SMR of 110 would suggest only a 10% excess mortality, which does not match the observed-to-expected ratio of 30:25. - The calculation clearly shows a ratio of 1.2, not 1.1. *130* - This option overestimates the SMR. - An SMR of 130 would require observed deaths to be 1.3 times the expected deaths (32.5 deaths expected for 30 observed). - The actual ratio is 30/25 = 1.2, making this value too high.

Question 767: Consider the following: 1. Standard deviation 2. Range 3. Mode 4. Median Among the above, which is/are the measure/measures of dispersion?

A. 3 and 4 only
B. 1 only
C. 1 and 2 only (Correct Answer)
D. 1, 2, 3 and 4

Explanation: ***1 and 2 only*** - The **standard deviation** quantifies the average amount of variability or dispersion around the mean, representing how spread out the data points are. - The **range** is the difference between the maximum and minimum values in a dataset, providing a simple measure of the total spread. *3 and 4 only* - The **mode** represents the most frequently occurring value in a dataset, which is a measure of central tendency, not dispersion. - The **median** is the middle value when data is ordered, also a measure of central tendency. *1 only* - While **standard deviation** is a measure of dispersion, this option incorrectly excludes the **range**, which also quantifies data spread. - Both **standard deviation** and **range** are fundamental measures used to describe the variability within a dataset. *1, 2, 3 and 4* - This option incorrectly includes the **mode** and **median**, which are measures of **central tendency**, not dispersion. - Measures of dispersion specifically describe the **spread or variability** of data, whereas central tendency measures describe the center of the data.

Question 768: In a normal curve, the area between one standard deviation on either side of the mean will include:

A. 70 – 85% of the values
B. 95% of the values
C. Approximately 68% of the values (Correct Answer)
D. Less than 50% of the values

Explanation: ***Approximately 68% of the values*** - In a **normal distribution** (bell curve), approximately **68% of data points** fall within one standard deviation ($\pm1\sigma$) from the mean. - This is a fundamental property of the **empirical rule** (or 68-95-99.7 rule) in statistics. *70 – 85% of the values* - This range is too broad and does not accurately reflect the specific percentage for **one standard deviation**. - While it overlaps with the correct value, it is not the precise percentage associated with $\pm1\sigma$. *95% of the values* - This percentage refers to the data included within **two standard deviations** ($\pm2\sigma$) from the mean in a normal distribution, not one. - The **empirical rule** states that approximately 95% of data falls within two standard deviations. *Less than 50% of the values* - This is incorrect, as the range of **one standard deviation** on either side of the mean covers more than half of the data. - The mean itself divides the data into two 50% halves, so incorporating any deviation around it will cover more than 50%.

Question 769: The relationship between birth rate and maternal hemoglobin is best studied by:

A. Sensitivity and specificity.
B. Correlation and regression. (Correct Answer)
C. Standard error of difference between two means.
D. Standard error of difference between two proportions.

Explanation: ***Correlation and regression.*** - **Correlation** measures the strength and direction of a linear relationship between two quantitative variables (birth rate and maternal hemoglobin levels). - **Regression analysis** allows for modeling the relationship between variables, enabling prediction of birth rate based on maternal hemoglobin, or vice versa, and quantifying the effect of one on the other. *Sensitivity and specificity.* - These concepts are used to evaluate the performance of a **diagnostic test** or screening tool in correctly identifying individuals with and without a specific condition. - They are not appropriate for studying the relationship between two continuous variables like birth rate and maternal hemoglobin. *Standard error of difference between two means.* - This statistical measure is used to determine if there is a **statistically significant difference** between the means of two independent groups, typically when comparing a quantitative outcome between these groups. - It is not suitable for assessing the continuous relationship or association between two continuous variables. *Standard error of difference between two proportions.* - This measure is employed to assess whether there is a **statistically significant difference** between the proportions or percentages of an outcome in two different groups. - It is used for categorical data and is not applicable for analyzing the relationship between two continuous variables.

Question 770: Which of the following statements is true about direct age standardization?

A. Number of people in each age group is not known
B. Age specific death rates are not known
C. A standard population is used (Correct Answer)
D. Standardized mortality ratio is used

Explanation: ***A standard population is used*** - In **direct age standardization**, age-specific death rates from the study population are applied to a **standard population's** age distribution to calculate an expected number of events. - This method helps to compare mortality or morbidity across different populations by removing the confounding effect of differing age structures. *Number of people in each age group is not known* - This statement is incorrect; to apply the study population's age-specific rates to the standard population, the **number of people in each age group of the standard population must be known**. - Without this demographic information, direct age standardization cannot be performed effectively. *Age specific death rates are not known* - This statement is incorrect because **age-specific death rates** for the *study population* are a prerequisite for direct age standardization. - These rates are multiplied by the corresponding age groups of a **standard population** to calculate standardized rates. *Standardized mortality ratio is used* - The **Standardized Mortality Ratio (SMR)** is a measure used in *indirect* age standardization, not direct age standardization. - SMR compares the number of observed deaths in a study population to the number expected if the study population had the same age-specific death rates as a **standard population**.

Practice by Chapter

Collection and Presentation of Data

Practice Questions

Measures of Central Tendency

Practice Questions

Measures of Dispersion

Practice Questions

Normal Distribution

Practice Questions

Sampling Methods

Practice Questions

Sample Size Calculation

Practice Questions

Hypothesis Testing

Practice Questions

Tests of Significance

Practice Questions

Correlation and Regression

Practice Questions

Survival Analysis

Practice Questions

Multivariate Analysis

Practice Questions

Statistical Software in Research

Practice Questions

Want unlimited practice?

Get full access to all questions, explanations, and performance tracking.

Start For Free