Biostatistics Practice Questions

Q: Percentiles divide data into how many equal parts?

Hundred. **Explanation:** In biostatistics, **Percentiles** are measures of central tendency (specifically, positional averages) that divide a frequency distribution into **100 equal parts**. Each part represents 1% of the total data set. There are 99 percentiles (P1 to P99) that create these 100 divisions. **Analysis of Options:** * **Option D (Correct):** Percentiles divide the data into **100 parts**. For example, the 50th percentile (P50) is the point below which 50% of the observations lie. * **Option A (Incorrect):** The **Median** divides data into **two** equal parts. * **Option B (Incorrect):** **Quartiles** divide data into **four** equal parts (Q1, Q2, and Q3). * **Option C (Incorrect):** This is a distractor. While the 50th percentile is the Median, it does not represent the total number of divisions. **High-Yield NEET-PG Pearls:** 1. **Median = 50th Percentile = 2nd Quartile (Q2).** 2. **Interquartile Range (IQR):** Represents the middle 50% of the data (Q3 – Q1). It is the preferred measure of dispersion for skewed data. 3. **Clinical Application:** Percentiles are most commonly used in **Growth Charts** (e.g., WHO/IAP charts). A child on the 95th percentile for weight is heavier than 95% of children of the same age and sex. 4. **Deciles:** Divide data into **10 equal parts** (D1 to D9).

Q: What does the standard deviation of the means measure?

Sampling error. ### Explanation **1. Why the correct answer is right:** The "standard deviation of the means" is technically known as the **Standard Error of Mean (SEM)**. In biostatistics, when we take multiple random samples from a single population, the means of these samples will vary slightly from one another. This variation is called **Sampling Error**. The SEM quantifies how much a sample mean is likely to deviate from the true population mean. It is calculated as: $SEM = \frac{SD}{\sqrt{n}}$ (where $SD$ is the standard deviation of the sample and $n$ is the sample size). Therefore, the standard deviation of the distribution of sample means directly measures the magnitude of the sampling error. **2. Why the incorrect options are wrong:** * **A. Non-sampling errors:** These occur due to human mistakes, such as faulty data collection, observer bias, or incorrect data entry. They can occur even in a census and are not measured by the standard deviation of means. * **C. Random errors:** While sampling error is a type of random variation, "Random error" is a broader term that includes unpredictable fluctuations in measurement (precision). SEM specifically addresses the error arising from the sampling process itself. * **D. Conceptual errors:** These relate to flaws in the study design, hypothesis formulation, or the theoretical framework, which cannot be quantified by standard deviation. **3. High-Yield Clinical Pearls for NEET-PG:** * **Standard Deviation (SD)** measures the scatter of individual observations around the mean within a single sample. * **Standard Error (SE)** measures the scatter of sample means around the true population mean. * As the **sample size ($n$) increases**, the Standard Error **decreases**, meaning the sample mean becomes a more accurate estimate of the population mean. * SE is used to calculate **Confidence Intervals (CI)**. For a 95% CI, the range is $Mean \pm 1.96 \times SEM$.

Q: If the birth rate of a sub-centre serving a population of 5000 is 25 per 1000, what is the expected number of pregnancies in a year?

138. ### Explanation **1. Why Option C is Correct** To calculate the expected number of pregnancies in a community, we must account for both **live births** and **pregnancy wastage** (abortions and stillbirths). In public health planning, it is standard practice to add **10%** to the total number of live births to account for these losses. * **Step 1: Calculate Live Births** Birth Rate = (Number of Live Births / Total Population) × 1000 25 = (Live Births / 5000) × 1000 Live Births = (25 × 5000) / 1000 = **125 live births.** * **Step 2: Account for Pregnancy Wastage (10%)** Expected Pregnancies = Live Births + 10% of Live Births Expected Pregnancies = 125 + (0.10 × 125) = 125 + 12.5 = **137.5.** Rounding off gives **138**. **2. Analysis of Incorrect Options** * **Option A (69):** This is roughly half the correct value; it might result from using the wrong denominator or population base. * **Option B (125):** This represents only the number of **live births**. It is incorrect because it fails to account for pregnancies that do not result in a live birth (wastage). * **Option D (150):** This uses a 20% wastage factor, which is higher than the standard 10% used in national health programs for estimation. **3. NEET-PG High-Yield Pearls** * **Formula for Expected Pregnancies:** `[Total Population × CBR / 1000] + 10% wastage`. * **Sub-centre Norms:** In India, a sub-centre serves a population of 5,000 (plain area) or 3,000 (hilly/tribal area). * **Crude Birth Rate (CBR):** It is the simplest measure of fertility, but it is "crude" because the denominator includes the entire population (men, children, and elderly), not just those at risk of childbirth. * **Target Population:** Identifying the expected number of pregnancies is crucial for calculating the "Antenatal Care (ANC) registration" targets for ASHAs and ANMs.

Q: A researcher found a correlation between dietary factors and a disease by collecting data from food manufacturers and hospitals. What type of study is this?

Ecological study. ### Explanation **Why Ecological Study is Correct:** The hallmark of an **Ecological Study** (also known as a correlational study) is that the unit of observation is a **population or a group**, rather than an individual. In this scenario, the researcher is collecting aggregate data from food manufacturers (representing dietary patterns of a region/population) and hospitals (representing disease prevalence/incidence in that population). Since the data does not link specific dietary habits to specific individuals, it is an ecological study used to generate hypotheses about potential associations. **Analysis of Incorrect Options:** * **B. Cross-sectional Study:** This study uses the **individual** as the unit of observation. It measures exposure and outcome simultaneously in individuals at a single point in time (snapshot). * **C. Psephological Study:** This is a distractor. Psephology is the statistical study of **elections and voting patterns**, which is irrelevant to medical epidemiology. * **D. Experimental Study:** These involve an **intervention** (like a drug or vaccine) where the researcher controls the exposure to observe the effect. This scenario describes an observational approach using existing data. **High-Yield Clinical Pearls for NEET-PG:** * **Ecological Fallacy:** This is the most common pitfall of ecological studies. It occurs when an association observed at the population level is incorrectly assumed to apply to individuals (e.g., "Countries with high fat intake have high heart disease, therefore every person eating high fat will get heart disease"). * **Unit of Study:** * Ecological: Population/Group * Cross-sectional/Case-control/Cohort: Individual * Randomized Controlled Trial (RCT): Individual (usually) * Community Trial: Community * Ecological studies are the quickest and least expensive way to generate a **hypothesis**, but they cannot prove causation.

Q: A study found the Odds Ratio of maternal hypertension to be 1:5 for having an Intrauterine Growth Restriction (IUGR) fetus. What is the interpretation drawn?

Inverse association. **Explanation:** The core of this question lies in the interpretation of the **Odds Ratio (OR)**, which is the measure of association used in Case-Control studies. 1. **Why "Inverse Association" is correct:** The Odds Ratio is interpreted based on its relationship to the value of **1.0 (the null value)**: * **OR > 1:** Positive association (Risk factor). * **OR = 1:** No association. * **OR < 1:** Negative or **Inverse association** (Protective factor). In this case, the OR is **1:5**, which equals **0.2**. Since 0.2 is less than 1, it indicates that the exposure (maternal hypertension) is associated with a *lower* frequency of the outcome (IUGR) compared to the control group, representing an inverse relationship. 2. **Why other options are incorrect:** * **Positive association:** This would require an OR > 1 (e.g., OR = 5.0), meaning the exposure increases the risk of the outcome. * **Common association:** This is not a standard epidemiological term for interpreting OR. Frequency of association is determined by prevalence, not the ratio itself. * **Rare outcome:** While the Odds Ratio is a good estimate of Relative Risk when the outcome is rare (the "Rare Disease Assumption"), the OR value itself (0.2) describes the *direction* of the association, not the prevalence of the disease. **High-Yield Clinical Pearls for NEET-PG:** * **Odds Ratio (OR):** Calculated as $ad/bc$ (Cross-product ratio). * **Relative Risk (RR):** Used in Cohort studies; it measures the strength of association. * **Interpretation Tip:** If OR = 0.2, it means the exposure reduces the odds of the outcome by 80% (1 - 0.2 = 0.8). * **Note:** In clinical reality, maternal hypertension is actually a risk factor for IUGR (OR > 1); however, in the context of this specific numerical question, you must follow the mathematical value provided.

Q: During the demographic transition, demographic dividend is due to a decrease in which of the following?

Demographic burden. **Explanation:** The **Demographic Dividend** refers to the economic growth potential that results from shifts in a population’s age structure. This occurs during the demographic transition when fertility and mortality rates decline. **Why the correct answer is right:** The demographic dividend is primarily driven by a **decrease in the Demographic Burden** (also known as the Dependency Ratio). As birth rates fall, the proportion of young dependents (0-14 years) decreases, while the proportion of the working-age population (15-64 years) increases. When there are fewer children and elderly people to support relative to the number of productive workers, the "burden" on the economy lessens, allowing for increased savings, investment, and rapid economic growth. **Analysis of Incorrect Options:** * **Demographic Gain/Loss:** These are general terms describing population increases or decreases but are not standard technical terms used to define the mechanism behind the dividend. * **Demographic Bonus:** This is actually a **synonym** for demographic dividend itself. The dividend is the *result* (the bonus), whereas the question asks what *decrease* causes it. You do not get a dividend because a bonus decreases; you get it because the burden decreases. **High-Yield Facts for NEET-PG:** * **Dependency Ratio Formula:** $\frac{(\text{Population } 0\text{-}14) + (\text{Population } 65+)}{\text{Population } 15\text{-}64} \times 100$. * **Window of Opportunity:** The period when the dependency ratio is lowest is called the "Demographic Window." * **India's Status:** India is currently in the middle of its demographic dividend phase, which started around 2005-06 and is expected to last until 2055. * **Prerequisite:** A demographic dividend is not automatic; it requires investments in health, education, and job creation to be realized.

Q: Mean hemoglobin of a group of pregnant females is 10.6 gm/dL with a standard deviation of 2 gm/dL. What is the hemoglobin level below which 5% of pregnant females in this group will fall?

7.31 gm/dL. ### Explanation This question tests the application of the **Normal Distribution (Gaussian Curve)** in biostatistics. In a normal distribution, data is distributed symmetrically around the mean, and specific percentages of the population fall within defined standard deviations (SD). **1. Why Option A is correct:** To find the value below which the bottom 5% of a population falls, we look at the properties of a normal distribution. * **95% of the population** lies between **Mean ± 1.96 SD**. * This leaves 5% of the population in the "tails" (2.5% in the lower tail and 2.5% in the upper tail). * However, for a **one-tailed 5% cutoff** (the bottom 5%), the formula used is **Mean – 1.64 SD**. **Calculation:** * Mean = 10.6 gm/dL; SD = 2 gm/dL * Value = Mean – (1.64 × SD) * Value = 10.6 – (1.64 × 2) = 10.6 – 3.28 = **7.32 gm/dL** (Closest to 7.31). **2. Why other options are incorrect:** * **Option B (8.6 gm/dL):** This is Mean – 1 SD (10.6 - 2). Approximately 16% of the population falls below 1 SD. * **Option C (6.6 gm/dL):** This is Mean – 2 SD (10.6 - 4). Only 2.5% of the population falls below this level. * **Option D (5.0 gm/dL):** This is nearly 3 SD away from the mean, representing less than 0.15% of the population. **3. High-Yield Clinical Pearls for NEET-PG:** * **68%** of values lie within **Mean ± 1 SD**. * **95%** of values lie within **Mean ± 1.96 SD** (often rounded to 2 SD for simplicity in exams). * **99%** of values lie within **Mean ± 2.58 SD** (often rounded to 3 SD). * **Confidence Interval (CI):** The range within which the true population parameter is likely to fall. * **Standard Error (SE):** Calculated as $SD / \sqrt{n}$; it measures the dispersion of sample means around the population mean.

Q: The Cohort study is associated with which of the following measures of association?

Relative risk. ### Explanation **Correct Answer: C. Relative Risk** In epidemiology, a **Cohort Study** is a longitudinal, observational study that moves from **cause to effect** (exposure to outcome). Because the researcher starts with a group of individuals free of the disease and follows them over time, they can directly calculate the **Incidence** of the disease in both exposed and unexposed groups. * **Relative Risk (RR)** is the ratio of the incidence of the disease among the exposed to the incidence among the unexposed ($RR = \frac{I_e}{I_u}$). It is the primary measure of association used to determine the strength of the relationship between a risk factor and an outcome in cohort studies. **Why other options are incorrect:** * **A. Prevalence:** This is measured in **Cross-sectional studies**. It represents a "snapshot" of a population at a single point in time, measuring both old and new cases. * **B. Odds Ratio (OR):** This is the measure of association for **Case-control studies**. Since case-control studies start with the disease (effect to cause), incidence cannot be calculated; instead, we calculate the odds of exposure. * **D. Exposure rates:** While exposure is tracked in a cohort, "exposure rate" is not a standard measure of association. Cohort studies compare *outcome* rates based on exposure status. **High-Yield Clinical Pearls for NEET-PG:** * **Attributable Risk (AR):** Also calculated in cohort studies; it indicates the amount of disease that can be attributed to the exposure ($I_e - I_u$). * **Best Study for Rare Exposures:** Cohort Study. * **Best Study for Rare Diseases:** Case-control Study. * **Incidence:** Can *only* be calculated in a Cohort study (Prospective). * **Mnemonic:** **C**ohort = **R**elative **R**isk (Both have 'R'), **C**ase-control = **O**dds **R**atio.

Q: The chance of passing a genetic disease 'y' trait by affected parents to their children is 0.16. If they plan to have two children, what is the probability that both children will have the 'y' trait?

0.0256. ### Explanation **1. Why Option D is Correct:** This question is based on the **Multiplication Rule of Probability** for **independent events**. In genetics, the inheritance of a trait by one child does not influence the inheritance of the same trait by a subsequent sibling; each birth is an independent event. * Probability of the 1st child having the trait ($P_1$) = 0.16 * Probability of the 2nd child having the trait ($P_2$) = 0.16 * To find the probability of **both** events occurring (Event A **AND** Event B), we multiply the individual probabilities: * $0.16 \times 0.16 = \mathbf{0.0256}$ **2. Why Other Options are Incorrect:** * **Option A (0):** This would imply that it is impossible for both children to inherit the trait, which contradicts genetic principles. * **Option B (0.16):** This is the probability for a single child. It ignores the requirement that *both* children must have the trait. * **Option C (0.32):** This is the result of the **Addition Rule** ($0.16 + 0.16$). Addition is used for "Either/Or" scenarios (mutually exclusive events), not "Both/And" scenarios. **3. Clinical Pearls & High-Yield Facts for NEET-PG:** * **Independent Events:** In biostatistics, remember that "Nature has no memory." The risk of a genetic disorder (e.g., Autosomal Recessive = 25%) remains the same for every pregnancy, regardless of previous outcomes. * **Multiplication Rule (AND):** Used when you want to find the joint probability of two or more independent events occurring together. * **Addition Rule (OR):** Used when you want to find the probability of at least one of two mutually exclusive events occurring. * **Complementary Probability:** The probability of a child *not* having the trait is $1 - 0.16 = 0.84$. The probability that *neither* child has the trait would be $0.84 \times 0.84 = 0.7056$.

Question 1

A new drug with in vitro activity against HIV is tested on a population of patients with Western-blot confirmed HIV infections in Mumbai. Out of the 200 individuals in the patient population, 100 individuals are chosen randomly to receive the drug. The drug, which is tasteless, is administered in a cup of orange juice; the other patients receive pure orange juice. Neither the nurses, doctors, nor patients know which patients receive the drug. At the end of the study period, the number of CD4+ T cells is determined for all of the subjects. What is the research method used in this study?

Accepted Answer

Double-blind randomized clinical trial

Answer

Case-control study

Answer

Case report

Answer

Cohort study

Question 2

Percentiles divide data into how many equal parts?

Accepted Answer

Hundred

Answer

Two

Answer

Four

Answer

Fifty

Question 3

What does the standard deviation of the means measure?

Accepted Answer

Sampling error

Answer

Non-sampling errors

Answer

Random errors

Answer

Conceptual errors

Question 4

If the birth rate of a sub-centre serving a population of 5000 is 25 per 1000, what is the expected number of pregnancies in a year?

Accepted Answer

138

Answer

69

Answer

125

Answer

150

Question 5

A researcher found a correlation between dietary factors and a disease by collecting data from food manufacturers and hospitals. What type of study is this?

Accepted Answer

Ecological study

Answer

Cross-sectional study

Answer

Psephological study

Answer

Experimental study

Question 6

A study found the Odds Ratio of maternal hypertension to be 1:5 for having an Intrauterine Growth Restriction (IUGR) fetus. What is the interpretation drawn?

Accepted Answer

Inverse association

Answer

Positive association

Answer

Common association

Answer

Rare outcome

Question 7

During the demographic transition, demographic dividend is due to a decrease in which of the following?

Accepted Answer

Demographic burden

Answer

Demographic gain

Answer

Demographic loss

Answer

Demographic bonus

Question 8

Mean hemoglobin of a group of pregnant females is 10.6 gm/dL with a standard deviation of 2 gm/dL. What is the hemoglobin level below which 5% of pregnant females in this group will fall?

Accepted Answer

7.31 gm/dL

Answer

8.6 gm/dL

Answer

6.6 gm/dL

Answer

5.0 gm/dL

Question 9

The Cohort study is associated with which of the following measures of association?

Accepted Answer

Relative risk

Answer

Prevalence

Answer

Odds ratio

Answer

Exposure rates

Question 10

The chance of passing a genetic disease 'y' trait by affected parents to their children is 0.16. If they plan to have two children, what is the probability that both children will have the 'y' trait?

Accepted Answer

0.0256

Answer

0

Answer

0.16

Answer

0.32

Biostatistics — MCQs

Biostatistics — MCQs

On this page

Practice by Chapter

Want unlimited practice?