Biostatistics Practice Questions

Q: Which of the following graphical methods is best for studying the decline in the percentage of alcohol usage in men and women over several years?

Line diagram. ### Explanation **1. Why the Correct Answer is Right:** The **Line Diagram** (or Line Graph) is the most suitable method for representing **trends over time**. In biostatistics, when we need to observe the progression, decline, or fluctuation of a variable (like alcohol usage percentage) across several years, a line diagram effectively connects data points to show the direction of change. It is particularly useful for comparing two or more groups (men vs. women) on the same axes, allowing for a clear visual comparison of their respective trends. **2. Why Other Options are Incorrect:** * **Pie Chart:** This is used to show the **proportional distribution** of a single variable at a specific point in time (e.g., the share of different types of substances used). It cannot represent changes over a time series. * **Histogram:** This is used for **continuous quantitative data** to show frequency distribution within a single group. It consists of adjacent rectangles where the area represents the frequency. It is not designed to show trends over years. * **Frequency Polygon:** This is a derivative of the histogram, created by joining the midpoints of the tops of the histogram bars. While it shows distribution, it is used for frequency data, not for tracking a percentage trend over a chronological period. **3. Clinical Pearls & High-Yield Facts for NEET-PG:** * **Trend over time:** Always choose **Line Diagram**. * **Correlation between two variables:** Always choose **Scatter Diagram**. * **Comparison of discrete/qualitative data:** Use a **Bar Chart**. * **Frequency distribution of continuous data:** Use a **Histogram**. * **To find Median graphically:** Use an **Ogive** (Cumulative frequency curve). * **Pictogram:** Uses images to represent data; easiest for a layperson to understand but least accurate.

Q: All of the following features are true about a cross-sectional study EXCEPT?

A cause and effect relationship can be established. ### Explanation **Why Option D is the Correct Answer (The "Except" Statement):** A cross-sectional study is often referred to as a **"Snapshot Study"** because it measures both the exposure and the outcome simultaneously at a single point in time. Because both are measured together, it is impossible to determine whether the exposure preceded the outcome. This lack of **temporality** (the first criterion of Bradford Hill’s criteria for causation) means that a cross-sectional study can show an **association** but cannot establish a definitive **cause-and-effect relationship**. **Analysis of Incorrect Options:** * **Option A:** This is a defining feature. It examines the prevalence of a condition in a population at one specific point in time (like a still photograph). * **Option B:** Unlike cohort studies, there is no forward-looking component. Once the data is collected from the participants, the study is complete; hence, follow-up is not required. * **Option C:** These studies are ideal for chronic conditions (e.g., Diabetes, Hypertension) because they measure **prevalence**. They are less useful for acute or rare diseases, as the "snapshot" might miss short-lived cases. **High-Yield Clinical Pearls for NEET-PG:** * **Prevalence Study:** Cross-sectional study is the best design to calculate the prevalence of a disease. * **Hypothesis Generation:** It is used to generate hypotheses, whereas analytical studies (Case-control/Cohort) are used to test them. * **Sequence of Strength:** Cross-sectional < Case-Control < Cohort < Randomized Controlled Trial (RCT). * **Ecological Fallacy:** Often associated with ecological studies, but remember that cross-sectional studies focus on individuals, not populations.

Q: If the mean, median, and mode are 10, 18, and 26 respectively, what kind of distribution is it?

Negatively skewed. ### Explanation **1. Why the Correct Answer is Right:** In biostatistics, the relationship between the **Mean, Median, and Mode** determines the shape of a frequency distribution curve. * In this question: **Mean (10) < Median (18) < Mode (26).** * When the mean is pulled toward the lower values (the left side), it indicates a **Negatively Skewed Distribution** (also known as "Left-skewed"). * The "tail" of the graph points toward the smaller numbers (negative side of the X-axis). This happens when there are a few extremely low values that drag the mean down, while the majority of data points are clustered at the higher end. **2. Why the Incorrect Options are Wrong:** * **Symmetric / Normal Distribution (Options A & B):** In a perfectly symmetrical or Normal (Gaussian) distribution, the **Mean = Median = Mode**. Since 10 ≠ 18 ≠ 26, the distribution is asymmetrical. * **Positively Skewed (Option C):** In a positively skewed distribution (Right-skewed), the relationship is reversed: **Mean > Median > Mode**. The tail points toward the higher values (positive side), usually due to a few extremely high outliers. **3. NEET-PG Clinical Pearls & High-Yield Facts:** * **The "Alphabetical Rule":** To remember the order in a **Positively Skewed** distribution, follow the alphabet: **M**ean > **M**edian > **M**ode (alphabetical order of the second letters: e > i > o). * **Median's Position:** In any skewed distribution (positive or negative), the **Median always stays in the middle** between the Mean and the Mode. * **Best Measure of Central Tendency:** * For **Normal Distribution**: Mean is the best measure. * For **Skewed Distribution**: Median is the best measure (as it is not affected by extreme outliers). * **Formula (Karl Pearson’s):** $Mode = (3 \times Median) - (2 \times Mean)$. This is often used to calculate a missing value in NEET-PG numericals.

Q: At the end of the year 1990, the population of a primary health centre was 30,000 and there were 120 cases of pulmonary tuberculosis. At the end of the year 1991, the population was 30,600, 30 new cases were detected, and 2 cases had died. Based on this data, all of the following rates can be calculated EXCEPT?

Proportional mortality rate. To solve this question, we must understand the specific data requirements for various epidemiological indicators. ### **Why Proportional Mortality Rate (PMR) is the Correct Answer** **Proportional Mortality Rate** is defined as the number of deaths due to a specific cause (e.g., TB) divided by the **total number of deaths** from all causes in that population during the same period. * **The Missing Link:** While we know 2 people died of TB, the question does not provide the **total deaths from all causes** in the PHC. Without this denominator, PMR cannot be calculated. ### **Analysis of Incorrect Options** * **A. Incidence Rate:** This is the number of **new cases** (30) occurring in a population at risk during a specific period. Since we have the new cases and the mid-year population (approx. 30,300), this can be calculated. * **B. Prevalence Rate:** This includes **all cases** (old + new) existing at a point in time. At the end of 1991, the prevalence would be (120 old + 30 new - 2 deaths) divided by the total population. Thus, it is calculable. * **C. Case Fatality Rate (CFR):** This measures the killing power of a disease. It is calculated as (Deaths due to TB / Total cases of TB) × 100. Here, (2 / 150) × 100 provides the CFR. ### **High-Yield Clinical Pearls for NEET-PG** 1. **Incidence vs. Prevalence:** Incidence is a measure of **rate** (new cases/waterfall), while Prevalence is a measure of **proportion** (total cases/pool). 2. **PMR vs. CFR:** PMR indicates the *burden* of a specific disease relative to all deaths in a community, whereas CFR indicates the *severity* of the disease among those afflicted. 3. **Denominator Check:** Always look for "Total Deaths" for PMR and "Total Population" for Crude Death Rate. If neither is present, mortality rates (except CFR) usually cannot be calculated.

Q: In an investigation to study the effect of smoking on renal cell carcinoma, it is observed that 30 out of 50 patients were smokers as compared to 10 out of 50 control subjects. What is the odd ratio of renal cell carcinoma associated with smoking?

6. ### Explanation **1. Understanding the Correct Answer (C: 6)** The study design described is a **Case-Control Study**, as it starts with known cases (Renal Cell Carcinoma) and compares them to controls to look back at an exposure (smoking). The appropriate measure of association for such studies is the **Odds Ratio (OR)**. To calculate the Odds Ratio, we use a 2x2 contingency table: | | Cases (RCC) | Controls | | :--- | :---: | :---: | | **Exposed (Smokers)** | 30 (a) | 10 (b) | | **Non-Exposed (Non-smokers)** | 20 (c) | 40 (d) | | **Total** | 50 | 50 | * **Formula:** $OR = \frac{ad}{bc}$ (Cross-product ratio) * **Calculation:** $OR = \frac{30 \times 40}{10 \times 20} = \frac{1200}{200} = 6$ * **Interpretation:** Smokers have 6 times higher odds of developing renal cell carcinoma compared to non-smokers. **2. Why Other Options are Incorrect** * **Option A (3):** This is a common error where students simply divide the number of exposed cases by exposed controls ($30/10$). This ignores the non-exposed group. * **Option B (0.33):** This is the inverse of 3 ($1/3$), often resulting from flipping the numerator and denominator. * **Option D (0.16):** This is the inverse of 6 ($1/6$), representing the odds of the control group rather than the cases. **3. High-Yield Clinical Pearls for NEET-PG** * **Odds Ratio (OR):** Used in Case-Control studies. It is an estimate of Relative Risk (RR). * **Relative Risk (RR):** Used in Cohort studies. It cannot be calculated in case-control studies because the incidence cannot be determined. * **Attributable Risk (AR):** Indicates the amount of disease that can be attributed to the exposure. * **Key Rule:** If OR > 1, the exposure is a risk factor. If OR = 1, there is no association. If OR < 1, the exposure is protective.

Q: The mean of 25 plasma volumes is 12.5 litres. The standard deviation is 0.25. Calculate the variance.

0.0625. ### Explanation **1. Why the correct answer is right:** In biostatistics, **Variance** is a measure of the dispersion of data points around the mean. It is mathematically defined as the **square of the Standard Deviation (SD)**. The formula is: $$\text{Variance} = (\text{Standard Deviation})^2$$ Given in the question: * Standard Deviation (SD) = 0.25 * Variance = $(0.25)^2$ * Variance = $0.25 \times 0.25 = \mathbf{0.0625}$ Note that the "Mean" (12.5 litres) and the "Sample size" (25) are provided as distractors; they are not required for calculating variance when the SD is already known. **2. Why the incorrect options are wrong:** * **Option B (0.625):** This is a common calculation error where the decimal point is misplaced. * **Option C (6.25):** This occurs if one squares 2.5 instead of 0.25. * **Option D (625):** This occurs if the decimal point is ignored entirely ($25^2$). **3. Clinical Pearls & High-Yield Facts for NEET-PG:** * **Standard Deviation (SD):** It is the square root of variance. It is preferred over variance in clinical reports because it is expressed in the **same units** as the original data (e.g., litres), whereas variance is expressed in units squared (e.g., litres²). * **Coefficient of Variation (CV):** A measure of relative variation, calculated as $(SD / \text{Mean}) \times 100$. It is unitless and used to compare the variability of two different datasets. * **Standard Error of Mean (SEM):** Calculated as $SD / \sqrt{n}$. It measures how far the sample mean is likely to be from the true population mean. * **Normal Distribution:** In a Gaussian curve, Mean = Median = Mode. Approximately 95% of values lie within Mean ± 2 SD.

Q: In a population of 200 people with a normal distribution, how many people would be included within 1 standard deviation?

136. ### Explanation **1. Understanding the Correct Answer (A):** This question is based on the properties of a **Normal Distribution (Gaussian Distribution)** curve. In a normal distribution, the data is symmetrically distributed around the mean. According to the **Empirical Rule**: * **Mean ± 1 Standard Deviation (SD)** covers approximately **68.2%** of the population. * **Mean ± 2 SD** covers approximately **95.4%** of the population. * **Mean ± 3 SD** covers approximately **99.7%** of the population. To find the number of people within 1 SD in a population of 200: Calculation: $200 \times 68.2\% = 200 \times 0.682 = \mathbf{136.4}$. Rounding to the nearest whole number gives **136**. **2. Analysis of Incorrect Options:** * **Option B (140) and C (150):** These numbers are higher than the 68.2% threshold. They do not correspond to any standard sigma levels in biostatistics. * **Option D (190):** This represents 95% of the population ($200 \times 0.95 = 190$). This would be the approximate number of people included within **2 Standard Deviations** (specifically 1.96 SD), not 1 SD. **3. NEET-PG High-Yield Clinical Pearls:** * **Symmetry:** In a normal distribution, Mean = Median = Mode. * **Skewness:** If the tail is towards the right, it is **Positively Skewed** (Mean > Median > Mode). If the tail is towards the left, it is **Negatively Skewed** (Mode > Median > Mean). * **Standard Normal Curve:** A normal curve with a Mean of 0 and an SD of 1. * **Z-score:** Indicates how many standard deviations an observation is from the mean. For 1 SD, $Z = 1$.

Question 1

Which of the following graphical methods is best for studying the decline in the percentage of alcohol usage in men and women over several years?

Accepted Answer

Line diagram

Answer

Pie chart

Answer

Histogram

Answer

Frequency polygon

Question 2

All of the following features are true about a cross-sectional study EXCEPT?

Accepted Answer

A cause and effect relationship can be established

Answer

All cases are seen at one point in time

Answer

Follow-up is not a necessary feature

Answer

More useful for chronic diseases

Question 3

If the mean, median, and mode are 10, 18, and 26 respectively, what kind of distribution is it?

Accepted Answer

Negatively skewed

Answer

Symmetric

Answer

Normal

Answer

Positively skewed

Question 4

At the end of the year 1990, the population of a primary health centre was 30,000 and there were 120 cases of pulmonary tuberculosis. At the end of the year 1991, the population was 30,600, 30 new cases were detected, and 2 cases had died. Based on this data, all of the following rates can be calculated EXCEPT?

Accepted Answer

Proportional mortality rate

Answer

Incidence rate

Answer

Prevalence rate

Answer

Case fatality rate

Question 5

If the specificity of a diagnostic test increases, what happens to the number of false negatives?

Accepted Answer

False negatives increase

Answer

False negatives decrease

Answer

True negatives decrease

Answer

False positives increase

Question 6

Which of the following is FALSE regarding Randomised Control Trials?

Accepted Answer

Randomisation is done while selecting subjects for the study

Answer

Results of attrition are included in the analysis

Answer

Double blinding is the most common form of blinding observed

Answer

Cross-over design helps removing ethical concerns

Question 7

In an investigation to study the effect of smoking on renal cell carcinoma, it is observed that 30 out of 50 patients were smokers as compared to 10 out of 50 control subjects. What is the odd ratio of renal cell carcinoma associated with smoking?

Accepted Answer

6

Answer

3

Answer

0.33

Answer

0.16

Question 8

In a randomized controlled trial, what is the essential purpose of randomization?

Accepted Answer

To eliminate selection bias

Answer

To produce double blinding

Answer

To decrease the follow-up period

Answer

To decrease the sample size

Question 9

The mean of 25 plasma volumes is 12.5 litres. The standard deviation is 0.25. Calculate the variance.

Accepted Answer

0.0625

Answer

0.625

Answer

6.25

Answer

625

Question 10

In a population of 200 people with a normal distribution, how many people would be included within 1 standard deviation?

Accepted Answer

136

Answer

140

Answer

150

Answer

190

Biostatistics — MCQs

Biostatistics — MCQs

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