Biostatistics Practice Questions

Q: Sensitivity of a screening test measures:

True positive rate. **Explanation:** **Sensitivity** is defined as the ability of a screening test to correctly identify those who actually have the disease. It is the proportion of people with the disease who test positive. 1. **Why Option A is Correct:** Sensitivity is mathematically expressed as **[True Positives (TP) / (True Positives + False Negatives)]**. Since (TP + FN) represents the total number of diseased individuals, sensitivity directly measures the **True Positive Rate**. A test with high sensitivity is ideal for screening because it ensures that very few cases are missed (low false negatives). 2. **Why Other Options are Incorrect:** * **Option B (False Positive Rate):** This is calculated as (1 – Specificity). It represents the proportion of healthy individuals incorrectly identified as diseased. * **Option C (True Negative Rate):** This is the definition of **Specificity**. It measures the test's ability to correctly identify those without the disease. * **Option D (False Negative Rate):** This is calculated as (1 – Sensitivity). It represents the proportion of diseased individuals whom the test fails to identify. **Clinical Pearls for NEET-PG:** * **SNOUT:** A highly **S**ensitive test, when **N**egative, rules **OUT** the disease (useful for screening). * **SPIN:** A highly **SP**ecific test, when **P**ositive, rules **IN** the disease (useful for confirmation). * Sensitivity and Specificity are **inherent properties** of a test; they do not change with the prevalence of the disease in a population (unlike Predictive Values). * **Ideal Screening Test:** High sensitivity, low cost, and safe.

Q: Which of the following is the best measure of variability?

Standard deviation. ### Explanation **1. Why Standard Deviation (SD) is the correct answer:** In biostatistics, measures of variability (or dispersion) describe how spread out the data points are from the center. **Standard Deviation** is considered the best and most widely used measure of variability because: * It is based on all observations in the dataset. * It is mathematically stable and used in further statistical tests (like calculating the Standard Error). * It indicates how much, on average, each value deviates from the mean. In a normal distribution, approximately 68% of values lie within ±1 SD. **2. Why the other options are incorrect:** * **Mean, Mode, and Median (Options A, B, and C):** These are **Measures of Central Tendency**, not variability. They describe the "center" or "average" of a dataset but provide no information about how scattered the data points are. * **Mean:** The arithmetic average. * **Median:** The middle-most value (best for skewed data). * **Mode:** The most frequently occurring value. **3. High-Yield Clinical Pearls for NEET-PG:** * **Range:** The simplest but most unstable measure of variability (Difference between Maximum and Minimum). * **Variance:** The square of the Standard Deviation ($SD^2$). * **Coefficient of Variation (CV):** Used to compare the variability of two different series (e.g., comparing height in cm vs. weight in kg). Formula: $(SD / Mean) \times 100$. * **Standard Error (SE):** Measures the variability of sample means; it is always smaller than the SD. Formula: $SD / \sqrt{n}$. * **Ideal Measure:** While SD is the best for normally distributed data, the **Interquartile Range (IQR)** is the best measure of variability for skewed data.

Q: According to the 1991 census, what was the average family size?

5.5. **Explanation:** In Community Medicine and Demography, understanding historical census data is crucial for tracking population trends and planning public health interventions. **1. Why 5.5 is Correct:** According to the **1991 Census of India**, the average family size (household size) was recorded as **5.5**. This period was characterized by a high Total Fertility Rate (TFR) and the prevalence of joint or extended family systems in both rural and urban areas. Monitoring family size is a key demographic indicator used to calculate housing needs, per capita resource allocation, and the efficacy of family planning programs. **2. Analysis of Incorrect Options:** * **A (2.4):** This value is significantly lower than any recorded national average for India. For context, 2.1 is the "Replacement Level Fertility" goal, not the family size. * **C (4.4):** This represents a more modern figure. As per the **NFHS-5 (2019-21)**, the average household size in India has declined to approximately **4.4**, reflecting the transition toward nuclear families and lower fertility rates. * **D (5.9):** This figure is higher than the 1991 average. While some specific states or rural pockets may have reached this level, the national average remained at 5.5. **3. High-Yield Clinical Pearls for NEET-PG:** * **Definition:** A "Household" in the census refers to a group of persons who commonly live together and take their meals from a common kitchen. * **Trend:** India’s family size has shown a steady **downward trend** from 1991 (5.5) to 2001 (5.3), 2011 (4.8/4.9), and currently ~4.4 (NFHS-5). * **Demographic Transition:** The reduction in family size is a direct result of the demographic transition, specifically the decline in the Birth Rate and the success of the "Small Family Norm."

Q: Proportional mortality rate is:

Proportion. ### Explanation The correct answer is **Proportion**. **1. Why it is a Proportion:** Despite its name, **Proportional Mortality Rate (PMR)** is mathematically a proportion, not a rate. It measures the number of deaths due to a specific cause (or in a specific age group) relative to the **total number of deaths** from all causes in the same population during the same period. * **Formula:** (Deaths due to a specific cause / Total deaths from all causes) × 100. * Because the numerator (deaths from a specific cause) is a subset of the denominator (total deaths), it satisfies the definition of a proportion. It is usually expressed as a percentage. **2. Why other options are incorrect:** * **Rate:** A true rate (like Crude Death Rate) requires a "population at risk" in the denominator and a time component. PMR does not use the mid-year population; it only compares deaths to deaths. * **Ratio:** A ratio compares two independent entities (e.g., Male:Female ratio) where the numerator is not part of the denominator. In PMR, the specific deaths are inherently part of the total deaths. **3. NEET-PG High-Yield Pearls:** * **Indicator of Burden:** PMR is used to identify the leading causes of death in a community and to determine the relative importance of a specific disease. * **Case Fatality Rate (CFR):** Like PMR, CFR is also a **proportion**, even though it is called a "rate." It measures the killing power of a disease (Numerator: Deaths from disease; Denominator: Total cases of that disease). * **Key Distinction:** PMR is **not** a measure of the risk of dying from a disease (that is the Cause-Specific Mortality Rate); it only shows the composition of deaths.

Q: Mammography has 90% sensitivity and 98% specificity for breast carcinoma. What is the probability that a woman with breast carcinoma remains undiagnosed for 2 consecutive years?

1%. ### Explanation **1. Understanding the Correct Answer (1%)** To solve this, we must first identify the **False Negative Rate (FNR)**. * **Sensitivity** is the ability of a test to correctly identify those with the disease. Here, it is 90% (0.9). * The **False Negative Rate** is the probability that a person *with* the disease tests negative. It is calculated as: $1 - \text{Sensitivity}$. * $1 - 0.90 = 0.10$ (or 10%). The question asks for the probability of remaining undiagnosed for **two consecutive years**. Since each year's screening is an independent event, we use the **Multiplication Rule of Probability**: * Year 1 False Negative (0.10) × Year 2 False Negative (0.10) = **0.01 or 1%**. **2. Why Other Options are Incorrect** * **10% (Implicitly considered):** This represents the probability of a false negative in a single year. It fails to account for the second consecutive screening. * **2%:** This is a common distractor often confused with the complement of specificity (False Positive Rate). Specificity (98%) is irrelevant here because the question specifies the woman *has* breast carcinoma. * **0.1%:** This would be the result if the sensitivity were 99% ($0.01 \times 0.01$). **3. Clinical Pearls & High-Yield Facts for NEET-PG** * **Sensitivity (True Positive Rate):** Best for **screening** tests (SNOUT: Sensitivity rules OUT). * **Specificity (True Negative Rate):** Best for **confirmatory** tests (SPIN: Specificity rules IN). * **False Negative Rate (Type II Error/β):** The probability of missing a diagnosis. * **False Positive Rate (Type I Error/α):** Calculated as $1 - \text{Specificity}$. * **Sequential Testing:** When two tests are used in series (like yearly mammograms), the overall sensitivity decreases, but the overall specificity increases. However, the probability of a "miss" (False Negative) across multiple tests is the product of individual false negative rates.

Q: Twenty-five children are chosen randomly from a school playground. Their heights are measured in 2 consecutive months. What statistical test could be used to test the hypothesis that their heights are not different in consecutive months?

Paired t-test. ### Explanation **Why Paired t-test is the Correct Answer:** The core concept here is the **comparison of means in a "before-and-after" scenario** involving the same group of individuals. In this question, the same 25 children are measured twice (Month 1 and Month 2). Since the two sets of data are dependent (linked to the same person), we use the **Paired t-test**. This test evaluates whether the mean difference between these two related observations is significantly different from zero. **Analysis of Incorrect Options:** * **A. Unpaired t-test (Independent t-test):** This is used to compare the means of two **independent** groups (e.g., comparing heights of 25 children from School A with 25 different children from School B). * **C. Z-test:** While also used to compare means, a Z-test requires a **large sample size (n > 30)** and a known population variance. Here, the sample size is small (n = 25). * **D. Regression:** This is used to determine the **strength and direction of a relationship** between a dependent and independent variable (e.g., how much height increases for every year of age), rather than testing the difference between two sets of measurements. **High-Yield Clinical Pearls for NEET-PG:** * **Paired data** occurs in: Before-after studies, cross-over trials, and case-control studies with 1:1 matching. * **Parametric vs. Non-parametric:** If the data were not normally distributed, the non-parametric alternative to the Paired t-test would be the **Wilcoxon Signed-Rank Test**. * **Sample Size Rule:** Use **t-test** for n 30. * **ANOVA:** Use this when comparing means of **more than two** independent groups.

Question 1

Sensitivity of a screening test measures:

Accepted Answer

True positive rate

Answer

False positive rate

Answer

True negative rate

Answer

False negative rate

Question 2

All of the following are true regarding the Sample Registration System (SRS) EXCEPT:

Accepted Answer

Conducts an annual survey

Answer

Initiated in the 1960s

Answer

Estimates birth and death rates

Answer

Employs a dual-record system

Question 3

Which of the following is the best measure of variability?

Accepted Answer

Standard deviation

Answer

Mean

Answer

Mode

Answer

Median

Question 4

Which of the following is NOT included in the Human Development Index?

Accepted Answer

Life expectancy at birth

Answer

Gross National Income (GNI) per capita

Answer

Mean years of schooling and Expected years of schooling

Answer

Knowledge

Question 5

According to the 1991 census, what was the average family size?

Accepted Answer

5.5

Answer

2.4

Answer

4.4

Answer

5.9

Question 6

A box and whisker plot is also known as which of the following?

Accepted Answer

Five summary plot

Answer

Magical box

Answer

Four summary plot

Answer

None of the above

Question 7

Proportional mortality rate is:

Accepted Answer

Proportion

Answer

Rate

Answer

Ratio

Answer

None of the above

Question 8

In a given population, approximately 10% of all deaths in the age group 0 to 14 years were due to accidents and injuries. In the same population, 20% of all deaths in the age group 15 to 35 years were due to accidents and injuries. How many times is the risk of dying due to accidents and injuries among 15 to 35 years as compared to the 0-14 years age group?

Accepted Answer

Cannot be concluded from the data

Answer

2

Answer

0.5

Answer

1

Question 9

Mammography has 90% sensitivity and 98% specificity for breast carcinoma. What is the probability that a woman with breast carcinoma remains undiagnosed for 2 consecutive years?

Accepted Answer

1%

Answer

2%

Answer

2%

Question 10

Twenty-five children are chosen randomly from a school playground. Their heights are measured in 2 consecutive months. What statistical test could be used to test the hypothesis that their heights are not different in consecutive months?

Accepted Answer

Paired t-test

Answer

Unpaired t-test

Answer

Z-test

Answer

Regression

Biostatistics — MCQs

Biostatistics — MCQs

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