Biostatistics — MCQs

Biostatistics Indian Medical PG Practice Questions and MCQs

Question 891: What is the probability of selecting a patient who requires surgery from a total of 50 admissions, where 10 girls and 20 boys needed surgery?

A. 3/10
B. 3/5 (Correct Answer)
C. 1/2
D. 1/3

Explanation: ***3/5*** - The total number of patients requiring surgery is the sum of girls and boys who needed surgery: **10 (girls) + 20 (boys) = 30 patients**. - The probability is calculated by dividing the number of favorable outcomes (patients needing surgery) by the total number of possible outcomes (total admissions): **30 / 50 = 3/5**. *3/10* - This option would be correct if only 15 patients (e.g., 5 girls and 10 boys) needed surgery out of 50 admissions. - It incorrectly calculates the proportion of patients requiring surgery relative to the total admissions. *1/2* - This option would imply that **25 out of 50** patients required surgery, which contradicts the given numbers. - It represents a **50% probability**, which is not supported by the calculation of 30 patients out of 50. *1/3* - This option would be correct if approximately **17 out of 50** patients needed surgery (16.67 rounded), which is not the case here. - It misrepresents the ratio of patients needing surgery to the total admissions, as **30/50 simplifies to 3/5, not 1/3**.

Question 892: In the context of medical screening, how does a series testing approach affect the net sensitivity and net specificity of the screening methods?

A. Net sensitivity is decreased and net specificity is increased (Correct Answer)
B. Net sensitivity and net specificity are both increased
C. Net sensitivity is increased and net specificity is decreased
D. Net sensitivity remains the same and net specificity is increased

Explanation: ***Net sensitivity is decreased and net specificity is increased*** - In **series (sequential) testing**, a positive diagnosis requires **ALL tests to be positive**. If any single test is negative, the overall result is negative. - **Net sensitivity DECREASES** because a person with disease must test positive on all tests in the series. If they test negative on even one test, they become a false negative. Formula: Sensitivity_net = Sensitivity₁ × Sensitivity₂ (always lower than individual sensitivities) - **Net specificity INCREASES** because a person without disease needs only ONE negative test result to be correctly classified as negative. Formula: Specificity_net = 1 - [(1-Specificity₁) × (1-Specificity₂)] (always higher than individual specificities) - **Series testing is used when high specificity is needed** (to rule IN disease, confirm diagnosis, minimize false positives) *Net sensitivity is increased and net specificity is decreased* - This describes **parallel (simultaneous) testing**, not series testing - In parallel testing, a positive result on **ANY test** leads to positive diagnosis - Parallel testing increases sensitivity (catches more true positives) but decreases specificity (more false positives) - Parallel testing is used for screening when you don't want to miss cases *Net sensitivity and net specificity are both increased* - This is **mathematically impossible** in real-world testing scenarios - Sensitivity and specificity have an inverse relationship - improving one typically decreases the other - No testing strategy (series or parallel) can simultaneously increase both parameters above individual test values *Net sensitivity remains the same and net specificity is increased* - This is incorrect because series testing **always affects both** sensitivity and specificity - The multiplicative nature of series testing means sensitivity must decrease when multiple tests are required to be positive - You cannot maintain sensitivity while requiring agreement across multiple tests

Question 893: What does the term 'validity' mean in the context of indicators?

A. Indicators should reflect changes in the situation being evaluated.
B. Indicators must be capable of collecting relevant data.
C. It accurately measures the concept it is intended to assess. (Correct Answer)
D. The measurement should yield consistent results across different evaluators under similar conditions.

Explanation: ***It accurately measures the concept it is intended to assess.*** - **Validity** refers to the degree to which an indicator truly measures what it is supposed to measure. - A valid indicator provides an **accurate reflection** of the underlying concept or phenomenon it aims to quantify. *Indicators should reflect changes in the situation being evaluated.* - This statement describes the characteristic of an indicator's **sensitivity** or **responsiveness** to change, not its validity. - A sensitive indicator might still be invalid if it doesn't accurately measure the intended concept. *Indicators must be capable of collecting relevant data.* - This refers to the **feasibility** or **practicality** of an indicator, concerning the ease and ability to collect the necessary data. - While important for an indicator's utility, it does not define its validity in terms of accurate measurement. *The measurement should yield consistent results across different evaluators under similar conditions.* - This characteristic describes **reliability**, which is the consistency and reproducibility of a measurement, rather than its accuracy in measuring the intended concept. - An indicator can be reliable (consistent) but still not valid (not measuring the correct thing).

Question 894: What is the shape of a normal distribution curve?

A. J-shaped
B. U-shaped
C. Bell-shaped (Correct Answer)
D. None of the options

Explanation: ***Bell-shaped*** - A **normal distribution** is a **symmetric probability distribution** centered around its mean, with tails that taper off indefinitely. - The distinctive shape resembles a **bell**, with the highest point at the mean and gradually decreasing frequencies as values move away from the mean. *J-shaped* - A **J-shaped curve** typically describes a distribution where the frequency is highest at one end and then continuously decreases or increases to the other end. - This shape is not characteristic of the **symmetry** and **central tendency** observed in a normal distribution. *U-shaped* - A **U-shaped curve** indicates that frequencies are highest at both ends of the distribution and lowest in the middle. - This is the opposite of a **normal distribution**, where the highest frequency is at the center (mean). *None of the options* - The term **bell-shaped** accurately describes a normal distribution curve, making this option incorrect.

Question 895: What is the probability that a value chosen from a community will be above the median?

A. 0.5 (Correct Answer)
B. 1
C. 0.25
D. 0.6

Explanation: ***0.5*** - The **median** is defined as the value that divides a dataset into two equal halves. - This means that **50% of the values** in the dataset are below the median, and **50% are above** the median. *0.25* - This would imply that only 25% of the data lies above the median, which contradicts its definition as the midpoint. - The value 0.25 is typically associated with **quartiles**, not the median. *0.6* - This indicates that 60% of the values are above the median, which is inconsistent with the median's role in splitting data evenly. - Such a probability would suggest that the chosen value falls into the **upper 60% segment**, not simply above the median. *1* - A probability of 1 means that it is **certain** for a value to be above the median, which is incorrect. - This would only be true if all observed values were greater than the median, which is not possible as the median itself is a data point or derived from data points.

Question 896: In a clinical study evaluating a new diagnostic test for a disease, the test was found to have 60 true positives out of 100 positive results. What is the positive predictive value of the test?

A. 40/100
B. 60/100 (Correct Answer)
C. 40/300
D. 240/300

Explanation: ***60/100*** - The **positive predictive value (PPV)** is the proportion of **true positives** among all positive test results. - Given 60 true positives out of 100 positive results, the calculation is 60 divided by 100. *40/100* - This value would represent the number of **false positives** (positive test results that are actually negative) out of all positive test results, which is not the positive predictive value. - The PPV is specifically concerned with the reliability of a positive result indicating the presence of the disease. *40/300* - This fraction does not correspond to a standard measure of diagnostic test validity given the provided information regarding true positives and total positive results. - It might incorrectly combine disparate data points or represent a miscalculation based on other variables not supplied. *240/300* - This value is not derived from the provided numbers for true positives and total positive results in the context of positive predictive value. - It could potentially represent sensitivity or specificity calculations, but it is not the **positive predictive value**.

Question 897: Which of the following statements accurately describes a characteristic of a random sample?

A. Any member of a group to be studied has an equal chance of being included in the study. (Correct Answer)
B. Every nth name on a list is selected in a systematic manner.
C. Subjects in the study are volunteers who choose to participate.
D. A person in a control group cannot be a member of the experimental group.

Explanation: ***Any member of a group to be studied has an equal chance of being included in the study.*** - This statement accurately defines a **random sample**, where each individual in the population has an **equal probability** of being selected. - This equal chance helps ensure the sample is **representative** of the larger population, reducing **sampling bias**. *Every nth name on a list is selected in a systematic manner.* - This describes **systematic sampling**, a type of probability sampling, but not a pure random sample. - While it can be helpful, it's not the defining characteristic of a general random sample, which emphasizes **equal chance** for every individual. *Subjects in the study are volunteers who choose to participate.* - This describes a **convenience sample** or **voluntary sample**, which is **non-random** and highly susceptible to bias. - Voluntary samples do not ensure that every individual in the population has an equal chance of participation. *A person in a control group cannot be a member of the experimental group.* - This statement refers to the **design of experimental studies** (control vs. experimental groups), not the method of **random sampling**. - While true for experimental design, it doesn't describe a characteristic of how a random sample is initially selected from a population.

Question 898: Which of the following is not a characteristic of a systematic review?

A. Search for literature is compulsory using explicit search strategy
B. Critical appraisal is always criteria based
C. Meta analysis is always performed (Correct Answer)
D. Research questions always focused

Explanation: ***Meta-analysis is always performed*** - While **meta-analysis** is frequently a component of a systematic review, it is not always performed; it is only feasible when the included studies are sufficiently homogeneous and quantitative synthesis is appropriate. - A systematic review can identify, appraise, and synthesize evidence without statistically combining results, especially when studies are too **heterogeneous**. *Search for literature is compulsory using explicit search strategy* - A **comprehensive and explicit search strategy** is a defining characteristic of a systematic review, ensuring all relevant literature is included and bias is minimized. - This systematic approach helps to identify all studies on a given topic, regardless of their outcome. *Research questions always focused* - Systematic reviews are driven by **clearly defined and focused research questions** (often in PICO format: Population, Intervention, Comparison, Outcome) to guide the search, selection, and analysis processes. - A focused question ensures the review has a narrow scope, allowing for a thorough and relevant synthesis of the evidence. *Critical appraisal is always criteria-based* - **Critical appraisal** using predefined criteria (e.g., risk of bias tools) is a mandatory step in a systematic review to evaluate the methodological quality and validity of the included studies. - This systematic assessment helps to determine the strength of the evidence and its applicability.

Question 899: Which of the following is a non-probability sampling method?

A. Simple random sampling
B. Systematic random sampling
C. Cluster sampling
D. Quota sampling (Correct Answer)

Explanation: ***Quota sampling*** - In **quota sampling**, researchers select participants based on specific characteristics (e.g., age, gender, ethnicity) to ensure the sample reflects the population proportions of these characteristics. - This method is **non-probability** because the selection of individuals within each quota is not random, and not every member of the population has an equal chance of being selected. *Simple random sampling* - **Simple random sampling** is a **probability sampling method** where every member of the population has an equal and independent chance of being selected. - This is typically achieved through random number generators or drawing names from a hat. *Systematic random sampling* - **Systematic random sampling** is a **probability sampling method** where sample members are selected at regular intervals from a list of the population. - The starting point is chosen randomly, but subsequent selections follow a predetermined pattern, ensuring a systematic, yet random, selection. *Cluster sampling* - **Cluster sampling** is a **probability sampling method** where the population is divided into naturally occurring groups (clusters), and then a random sample of these clusters is chosen. - Once clusters are selected, all individuals within the chosen clusters, or a random sample of individuals from them, are included in the study.

Question 900: APGAR scores of 30 children are recorded in a hospital, and most of the readings are found to be 7 or above. What can be inferred about this data distribution?

A. Positively skewed data
B. Negatively skewed data (Correct Answer)
C. Normal distribution
D. Symmetrical data

Explanation: ***Negatively skewed data*** - A distribution is **negatively skewed** when the bulk of the data is concentrated at the **higher end** of the scale - In this case, most **APGAR scores are 7 or above** (out of maximum 10), indicating a **left-skewed or negatively skewed distribution** - The tail of the distribution extends toward the **lower values**, while the peak is at the **higher end** - In negatively skewed data: **Mean < Median < Mode** *Positively skewed data* - **Positively skewed data** would imply that most APGAR scores were at the **lower end** of the scale, with a tail extending toward higher values - This is contrary to the observation that most scores are 7 or above - In positively skewed data: **Mode < Median < Mean** *Normal distribution* - A **normal distribution** implies a **symmetrical bell-shaped curve** where data is evenly distributed around the mean - The description "most readings are 7 or above" clearly indicates an **asymmetrical distribution**, not a normal one - In normal distribution: **Mean = Median = Mode** *Symmetrical data* - **Symmetrical data** means the distribution is balanced, with equal spread on both sides of the center - The given condition that most readings are at the **higher end (7 or above)** signifies an **imbalance**, ruling out symmetry

Practice by Chapter

Collection and Presentation of Data

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Measures of Central Tendency

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Measures of Dispersion

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Normal Distribution

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Sampling Methods

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Sample Size Calculation

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Hypothesis Testing

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Tests of Significance

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Correlation and Regression

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Survival Analysis

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Multivariate Analysis

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Statistical Software in Research

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