Biostatistics Practice Questions

Q: In a group of 100 children, the mean weight is 15 kg and the standard deviation is 1.5 kg. Which one of the following is true?

95% of all children weigh between 12 kg and 18 kg.. This question tests your understanding of the **Normal Distribution (Gaussian Curve)**, a fundamental concept in biostatistics frequently tested in NEET-PG. ### **The Core Concept: Empirical Rule** In a normal distribution, data is distributed symmetrically around the mean. The relationship between the Mean and Standard Deviation (SD) determines the percentage of the population falling within specific ranges: * **Mean ± 1 SD:** Covers **68.3%** of the values. * **Mean ± 2 SD:** Covers **95.4%** (commonly rounded to 95%) of the values. * **Mean ± 3 SD:** Covers **99.7%** of the values. ### **Step-by-Step Calculation** Given: Mean = 15 kg; SD = 1.5 kg. To find the 95% confidence interval (Mean ± 2 SD): * Lower Limit: $15 - (2 \times 1.5) = 15 - 3 = \mathbf{12\text{ kg}}$ * Upper Limit: $15 + (2 \times 1.5) = 15 + 3 = \mathbf{18\text{ kg}}$ Thus, **95% of children weigh between 12 kg and 18 kg.** ### **Analysis of Incorrect Options** * **Option B & D:** The range 13.5–16.5 kg represents **Mean ± 1 SD** ($15 \pm 1.5$). This accounts for approximately **68%** of the children, not 95% or 99%. * **Option C:** The range 12–18 kg represents **Mean ± 2 SD**, which corresponds to **95%**, not 99%. For 99% (specifically 99.7%), the range would be Mean ± 3 SD (10.5–19.5 kg). ### **High-Yield Clinical Pearls for NEET-PG** 1. **Standard Normal Curve:** Has a Mean of 0 and a SD of 1. 2. **Z-score:** Indicates how many SDs a value is from the mean. A Z-score of 1.96 corresponds exactly to the 95% confidence limit. 3. **Symmetry:** In a perfectly normal distribution, **Mean = Median = Mode**. 4. **Skewness:** If Mean > Median, it is **Positively Skewed** (tail to the right); if Mean < Median, it is **Negatively Skewed** (tail to the left).

Q: A non-symmetrical frequency distribution is known as?

Skewed distribution. **Explanation:** In biostatistics, the shape of a frequency distribution is defined by its symmetry. **1. Why the correct answer is right:** A **Skewed distribution** occurs when the data is not distributed evenly around the central point, resulting in a "tail" on one side. This lack of symmetry means the mean, median, and mode do not coincide. * **Positively Skewed (Right-skewed):** The tail extends towards the right (higher values). Here, **Mean > Median > Mode**. * **Negatively Skewed (Left-skewed):** The tail extends towards the left (lower values). Here, **Mean < Median < Mode**. **2. Why the incorrect options are wrong:** * **Normal distribution:** This is a perfectly **symmetrical**, bell-shaped curve where the Mean, Median, and Mode are all equal and located at the center. * **Cumulative frequency distribution:** This is a type of representation (often an Ogive curve) that shows the running total of frequencies. It describes how many observations fall below a certain value, rather than the symmetry of the data itself. **High-Yield Clinical Pearls for NEET-PG:** * **Best measure of Central Tendency:** In a **Normal** distribution, it is the **Mean**. In a **Skewed** distribution, it is the **Median** (as it is least affected by extreme values/outliers). * **The "Tail" Rule:** The direction of the skew is always determined by the direction of the **long tail**, not the peak. * **Relationship Memory Trick:** In a positive skew, the **Mean** is "pulled" most toward the tail (highest value), while the **Mode** remains at the peak (lowest value).

Q: Two screening tests in series will increase which of the following?

Both Specificity and Positive predictive value. ### Explanation In screening, the arrangement of tests (Series vs. Parallel) significantly impacts the validity and predictive value of the diagnostic process. **Why Option D is Correct:** When tests are conducted in **Series**, a patient must test positive on the first test AND the second test to be considered "positive." 1. **Specificity Increases:** This "double-check" mechanism filters out false positives. Since it is harder to pass both tests, fewer healthy people are misdiagnosed as diseased, thereby increasing specificity. 2. **Positive Predictive Value (PPV) Increases:** PPV is directly proportional to specificity. By reducing false positives, the probability that a person with a positive result actually has the disease increases. **Why Other Options are Incorrect:** * **Option A & C:** **Sensitivity decreases** in series testing because a person must test positive twice; if they miss either test, they are labeled negative (increasing false negatives). Consequently, **Negative Predictive Value (NPV)** also tends to decrease or remain less optimized compared to parallel testing. * **Option B:** While specificity does increase, it is not the *only* parameter affected. The PPV increases as a mathematical consequence of the improved specificity. **High-Yield Clinical Pearls for NEET-PG:** * **Tests in Parallel:** (e.g., ordering an EKG and Troponin simultaneously) **Increases Sensitivity** and **NPV**. It is used when you don't want to miss a single case (e.g., emergency room). * **Tests in Series:** (e.g., ELISA followed by Western Blot for HIV) **Increases Specificity** and **PPV**. It is used when the treatment is risky or expensive, and you must be certain of the diagnosis. * **Mnemonic:** **S**eries = **S**pecificity (Both start with 'S'). **P**arallel = **S**ensitivity (Think: "Parallel protects against missing cases").

Q: If the first quartile of a dataset is 34, what percentage of observations will be greater than this value?

75%. ### Explanation **Concept of Quartiles** In biostatistics, quartiles are values that divide a dataset—ordered from lowest to highest—into four equal parts, each containing 25% of the observations. * **First Quartile (Q1):** Also known as the 25th percentile. It marks the point below which 25% of the data lies. * **Second Quartile (Q2):** The Median (50th percentile). * **Third Quartile (Q3):** The 75th percentile. **Why Option B is Correct** The question states that the first quartile (Q1) is 34. By definition, Q1 separates the lowest 25% of the data from the upper 75%. Therefore, if 25% of the observations are less than 34, then **75% (100% - 25%)** of the observations must be greater than 34. **Analysis of Incorrect Options** * **Option A (25%):** This represents the percentage of observations *less than* or equal to the first quartile, not greater than it. * **Option C (37%) & Option D (66%):** These values do not correspond to standard quartile divisions (25%, 50%, or 75%) and are mathematically incorrect in this context. **Clinical Pearls & High-Yield Facts for NEET-PG** 1. **Interquartile Range (IQR):** Calculated as $Q3 - Q1$. It represents the middle 50% of the data and is the preferred measure of dispersion for skewed distributions. 2. **Box-and-Whisker Plot:** This graphical representation specifically uses quartiles. The "box" represents the IQR, and the line inside the box represents the Median (Q2). 3. **Relationship with Percentiles:** * $Q1 = 25^{th}$ percentile * $Q2 = 50^{th}$ percentile (Median) * $Q3 = 75^{th}$ percentile 4. **Robustness:** Quartiles and the Median are "resistant" measures, meaning they are not influenced by extreme outliers, unlike the Mean and Standard Deviation.

Q: In a town with a population of 5000, 500 individuals had myopia on January 1, 2011. By December 31, 2011, 90 new cases of myopia were identified. What is the incidence of myopia in the town during 2011?

0.02. ### Explanation **1. Understanding the Correct Answer (B: 0.02)** Incidence measures the number of **new cases** occurring in a **population at risk** during a specific period. The formula is: $$\text{Incidence} = \frac{\text{Number of new cases during a specific period}}{\text{Population at risk during that period}} \times 1000$$ * **New Cases:** 90 * **Population at Risk:** This is the total population minus those who already have the disease (since they are no longer "at risk" of developing it). * Population at risk = $5000 (\text{Total}) - 500 (\text{Existing cases}) = 4500$. * **Calculation:** $90 / 4500 = 0.02$. **2. Analysis of Incorrect Options** * **Option A (0.018):** This is calculated by dividing new cases by the *total* population ($90/5000$). This is a common mistake; you must subtract the prevalent cases from the denominator to find the true population at risk. * **Option C (0.05):** This represents the **Point Prevalence** at the start of the year ($500/5000 = 0.1$) or a miscalculation of the data. * **Option D (18):** This is likely the result of calculating the rate per 1000 ($90/5000 \times 1000$), but it uses the wrong denominator and incorrect decimal placement for the requested value. **3. NEET-PG High-Yield Pearls** * **Incidence vs. Prevalence:** Incidence = New cases (Rate); Prevalence = All cases (Ratio). * **Denominator Rule:** Always exclude individuals who already have the disease or are immune (e.g., vaccinated) from the denominator when calculating incidence. * **Attack Rate:** A type of incidence rate used specifically during epidemics for a limited period (e.g., food poisoning). * **Relationship:** $\text{Prevalence} = \text{Incidence} \times \text{Mean Duration of disease } (P = I \times D)$. This is applicable for stable chronic conditions.

Q: In which of the following study designs does the case act as its own control?

Cross-over study. **Explanation:** In a **Cross-over study**, each participant receives two or more treatments in a sequential manner. The key feature is that after the first intervention and a subsequent "washout period," the participant switches to the alternative treatment. Because the same individual is monitored under both the intervention and the control conditions, the **case acts as its own control**. This design is highly efficient as it eliminates "inter-individual variation" (confounding factors like genetics, age, or lifestyle), requiring a smaller sample size to achieve statistical significance. **Analysis of Incorrect Options:** * **Retrospective study:** Usually refers to a case-control design where researchers look backward in time to find exposures. It compares two different groups of people (cases vs. controls). * **Prospective study:** Typically refers to a cohort study where a group is followed forward in time. It compares exposed individuals to a separate group of unexposed individuals. * **Case-control study:** This design compares a group of people with a disease (cases) to a separate group of people without the disease (controls). The controls are different individuals, not the cases themselves. **Clinical Pearls for NEET-PG:** * **Washout Period:** The time allowed for the first drug to be eliminated from the body to prevent a **"carry-over effect"** into the next phase. * **Suitability:** Cross-over studies are ideal for **chronic, stable conditions** (e.g., asthma, hypertension, migraine) but are **not** suitable for acute illnesses or conditions cured by the first treatment. * **Bias:** The main concern in cross-over trials is the "period effect" or "order effect."

Question 1

Specificity of a diagnostic test refers to its ability to correctly identify individuals without the disease. Which of the following does NOT represent a characteristic or aspect of specificity?

Accepted Answer

The proportion of true positives among those with the disease

Answer

Correctly identifying individuals without the disease (True Negatives)

Answer

The proportion of true negatives among those without the disease

Answer

An ideal screening test should aim for 100% specificity

Question 2

In a group of 100 children, the mean weight is 15 kg and the standard deviation is 1.5 kg. Which one of the following is true?

Accepted Answer

95% of all children weigh between 12 kg and 18 kg.

Answer

95% of all children weigh between 13.5 kg and 16.5 kg.

Answer

99% of all children weigh between 12 kg and 18 kg.

Answer

99% of all children weigh between 13.5 kg and 16.5 kg.

Question 3

A non-symmetrical frequency distribution is known as?

Accepted Answer

Skewed distribution

Answer

Normal distribution

Answer

Cumulative frequency distribution

Answer

None of the above

Question 4

Specificity of a screening test is the ability of a test to correctly identify which of the following?

Accepted Answer

Individuals who have the disease but are incorrectly identified as not having it (false negatives)

Answer

Individuals who do not have the disease (true negatives)

Answer

Individuals who have the disease (true positives)

Answer

Individuals who do not have the disease but are incorrectly identified as having it (false positives)

Question 5

According to the WHO-recommended Expanded Program on Immunization (EPI) Cluster sampling methodology for assessing primary immunization coverage, what is the age group of children surveyed?

Accepted Answer

12-23 months

Answer

0-12 months

Answer

6-12 months

Answer

9-12 months

Question 6

Two screening tests in series will increase which of the following?

Accepted Answer

Both Specificity and Positive predictive value

Answer

Sensitivity alone

Answer

Specificity alone

Answer

Both Sensitivity and Negative predictive value

Question 7

If the first quartile of a dataset is 34, what percentage of observations will be greater than this value?

Accepted Answer

75%

Answer

25%

Answer

37%

Answer

66%

Question 8

In a town with a population of 5000, 500 individuals had myopia on January 1, 2011. By December 31, 2011, 90 new cases of myopia were identified. What is the incidence of myopia in the town during 2011?

Accepted Answer

0.02

Answer

0.018

Answer

0.05

Answer

18

Question 9

In which of the following study designs does the case act as its own control?

Accepted Answer

Cross-over study

Answer

Retrospective study

Answer

Prospective study

Answer

Case-control study

Question 10

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

Biostatistics — MCQs

Biostatistics — MCQs

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