Biostatistics Practice Questions

Q: A village is divided into five relevant subgroups for the purpose of a survey. Individuals from each subgroup are then selected randomly. What is this type of sampling called?

Stratified sampling. ### Explanation **1. Why Stratified Sampling is Correct:** In **Stratified Random Sampling**, the heterogeneous population is first divided into non-overlapping, homogeneous subgroups called **"strata"** based on specific characteristics (e.g., age, gender, socio-economic status, or "relevant subgroups" as mentioned in the question). A **simple random sample** is then drawn from *each* of these strata. This ensures that every subgroup is adequately represented, reducing sampling error compared to simple random sampling. **2. Why Other Options are Incorrect:** * **Simple Random Sampling:** Every individual in the entire population has an equal chance of being selected. There is no prior division into subgroups. * **Cluster Sampling:** The population is divided into groups (clusters), usually based on geographical areas (e.g., villages, wards). Unlike stratified sampling, you randomly select a few *entire clusters* and survey everyone within them, rather than selecting individuals from every group. * **Systematic Sampling:** This involves selecting every $k^{th}$ individual (sampling interval) from a list, starting from a random point (e.g., every 5th person entering an OPD). **3. High-Yield Clinical Pearls for NEET-PG:** * **Stratified vs. Cluster:** In Stratified sampling, the groups are **homogeneous within** (similar people) but **heterogeneous between** (strata differ from each other). In Cluster sampling, groups are **heterogeneous within** but **homogeneous between** (each cluster is a mini-reflection of the population). * **Multistage Sampling:** This is the most common method used in large-scale national health surveys (like NFHS), involving a combination of sampling techniques. * **Precision:** Stratified sampling is generally more precise than simple random sampling because it accounts for variability between subgroups.

Q: What is true about the standard normal distribution?

The total area under the curve is equal to 1.. ### Explanation **1. Why Option A is Correct:** The Standard Normal Distribution (Z-distribution) is a specific type of probability density function. In statistics, the **total area under any probability curve must equal 1 (or 100%)**, representing the sum of all possible outcomes. This property is fundamental for calculating Z-scores and p-values, as the area under specific segments of the curve represents the probability of an observation falling within that range. **2. Why the Other Options are Incorrect:** * **Option B:** In a *Standard* Normal Distribution, the **Mean is always 0** and the Standard Deviation is 1. If the mean were 1, it would simply be a "Normal Distribution," not the "Standard" version. * **Option C:** The Normal Distribution is perfectly symmetrical. Therefore, the **Mean = Median = Mode**. The relationship "Mean > Median > Mode" describes a **Positively Skewed** distribution. * **Option D:** A distribution with a tail towards the right is **Positively Skewed**. The Standard Normal Distribution is bell-shaped and symmetrical with no skew; both tails extend infinitely but are identical in shape. **3. High-Yield Clinical Pearls for NEET-PG:** * **Z-score formula:** $Z = (x - \mu) / \sigma$. It tells you how many standard deviations a value is from the mean. * **Empirical Rule (68-95-99.7 Rule):** * Mean ± 1 SD covers **68.2%** of the area. * Mean ± 2 SD covers **95.4%** of the area. * Mean ± 3 SD covers **99.7%** of the area. * **Point of Inflection:** In a normal curve, this occurs at Mean ± 1 SD (where the curve changes from convex to concave). * **Standard Error:** As sample size increases, the standard error decreases, making the distribution narrower.

Q: Which of the following is true about a cohort study?

Incidence can be calculated. **Explanation:** A **Cohort Study** is an observational, analytical study design where a group of individuals (the cohort) is defined based on the presence or absence of exposure to a particular factor and followed forward in time to observe the development of an outcome. **Why Option A is correct:** In a cohort study, we start with a population that is **at risk** but free of the disease. Since we follow these individuals over a period to see how many new cases develop, we can directly measure the **Incidence** (number of new cases in a population at risk). This allows for the calculation of **Relative Risk (RR)** and **Attributable Risk (AR)**. **Why other options are incorrect:** * **Option B:** Cohort studies proceed from **Cause to Effect** (Prospective). It is the Case-Control study that proceeds from effect (disease) to cause (exposure). * **Option C:** Cohort studies are generally **expensive** because they require large sample sizes and long-term follow-up of healthy individuals. * **Option D:** They require a **longer time** than case-control studies because the investigator must wait for the disease to manifest after exposure. **High-Yield Clinical Pearls for NEET-PG:** * **Best for:** Rare exposures (not rare diseases). * **Key Measure:** Relative Risk (RR). If RR > 1, there is a positive association. * **Bias:** The most common bias in cohort studies is **Attrition Bias** (loss to follow-up). * **Nested Case-Control Study:** A case-control study conducted within a large cohort study; it is more economical and reduces selection bias.

Q: Interpret the statistical graph shown below:

Positive correlation. ***Positive correlation*** - In a **positive correlation**, as one variable increases, the other variable also increases, creating an **upward trending pattern** on the scatter plot. - The data points form a **linear pattern** sloping from bottom-left to top-right, indicating a **direct relationship** between the variables. *Negative correlation* - Shows a **downward trending pattern** where one variable increases while the other decreases. - Data points slope from **top-left to bottom-right**, indicating an **inverse relationship** between variables. *Absent correlation* - Data points are **randomly scattered** with no discernible pattern or trend. - The **correlation coefficient (r)** approaches **zero**, indicating no linear relationship between variables. *Spurious correlation* - Represents a **false association** between two variables that appear correlated but lack a true causal relationship. - Often occurs due to **confounding variables** or **coincidental patterns** in the data.

Q: If one variable is given, how can another variable be predicted?

Coefficient of regression. ### Explanation **1. Why the Correct Answer is Right:** The **Coefficient of Regression ($b$)** is the correct answer because it quantifies the functional relationship between two variables. In a regression analysis, we use a mathematical equation (e.g., $Y = a + bX$) to describe how a dependent variable ($Y$) changes in response to an independent variable ($X$). Therefore, if the value of one variable is known, the regression coefficient allows us to **predict** the value of the other. **2. Why the Other Options are Wrong:** * **Coefficient of Variation (CV):** This measures the relative dispersion or "spread" of data ($CV = \frac{SD}{Mean} \times 100$). It is used to compare the variability between two different datasets (e.g., comparing the variability of height vs. weight), not for prediction. * **Coefficient of Correlation ($r$):** This measures the **strength and direction** of a linear relationship between two variables. While it tells us how closely they move together (from -1 to +1), it does not provide a mathematical formula to predict one from the other. * **Coefficient of Determination ($r^2$):** This represents the proportion of the variance in the dependent variable that is predictable from the independent variable. It indicates the "goodness of fit" of the model but is not the tool used for the actual prediction calculation. **3. High-Yield Clinical Pearls for NEET-PG:** * **Correlation ($r$)** = Degree of association; **Regression ($b$)** = Prediction of value. * The value of $r$ always lies between **-1 and +1**. * The value of $r^2$ (Determination) always lies between **0 and 1**. * If $r = 0.8$, then $r^2 = 0.64$, meaning 64% of the variation in $Y$ is explained by $X$. * **Scatter Diagram:** The best visual method to represent the relationship between two continuous variables before performing regression.

Q: Regarding the normal curve, which of the following statements is/are true?

Both limbs of the curve touch the baseline. ### Explanation The **Normal Distribution Curve** (also known as the Gaussian distribution) is a fundamental concept in biostatistics used to describe the distribution of continuous biological variables like height, blood pressure, or hemoglobin levels. **Why Option A is the Correct Answer:** In a theoretical normal distribution, the curve is **asymptotic** to the baseline. This means that the "tails" or limbs of the curve extend infinitely in both directions, getting closer and closer to the horizontal axis but **never actually touching or crossing it**. Therefore, the statement that the limbs touch the baseline is **mathematically false**, making it the correct choice for a "which is false" style question (common in NEET-PG patterns) or the specific outlier in this set. **Analysis of Other Options:** * **Option B (Symmetrical):** This is a **true** property. The curve is bell-shaped and perfectly symmetrical around the center. The left half is a mirror image of the right half. * **Option C (Skewness):** This is **false**. A normal curve has **zero skewness**. If a curve is skewed to the right (positive skew) or left (negative skew), it is by definition no longer a "Normal" curve. * **Option D (Mean, Median, Mode):** This is a **true** property. In a perfectly normal distribution, the mean, median, and mode are all equal and located at the peak of the curve. **High-Yield Clinical Pearls for NEET-PG:** 1. **Standard Deviation (SD) Limits:** * Mean ± 1 SD covers **68.3%** of values. * Mean ± 2 SD covers **95.4%** of values. * Mean ± 3 SD covers **99.7%** of values. 2. **Total Area:** The total area under the normal curve is equal to **1 (or 100%)**. 3. **Z-Score:** This indicates how many standard deviations a data point is from the mean. 4. **Point of Inflection:** The point where the curve changes from convex to concave occurs at **Mean ± 1 SD**.

Q: A diagnostic test was performed on 150 individuals. The results are presented in the table below: | Test Result | Disease Present | Disease Absent | |---|---|---| | Positive Test | 40 | 5 | | Negative Test | 10 | 95 | What is the specificity of this test?

0.95. ### Explanation **1. Understanding the Correct Answer (D: 0.95)** Specificity is the ability of a diagnostic test to correctly identify those **without the disease** (True Negatives). It is calculated as the proportion of people who are truly healthy and also test negative. The formula for Specificity is: $$\text{Specificity} = \frac{\text{True Negatives (TN)}}{\text{True Negatives (TN)} + \text{False Positives (FP)}}$$ From the table: * **True Negatives (TN):** 95 (Disease absent and test negative) * **False Positives (FP):** 5 (Disease absent but test positive) * **Calculation:** $95 / (95 + 5) = 95 / 100 = \mathbf{0.95}$ (or 95%). **2. Analysis of Incorrect Options** * **Option A (0.05):** This represents the **False Positive Rate** ($1 - \text{Specificity}$). It is the proportion of healthy individuals wrongly identified as diseased. * **Option B (0.4):** This is the **Positive Predictive Value (PPV)** if calculated incorrectly using only the diseased column, or a miscalculation of sensitivity. * **Option C (0.8):** This is the **Sensitivity** of the test. Sensitivity measures the ability to correctly identify those **with the disease** ($40 / [40+10] = 0.8$). **3. Clinical Pearls for NEET-PG** * **SNOUT:** **S**ensitivity rules **OUT** (High sensitivity means a negative result reliably excludes the disease). * **SPIN:** **S**pecificity rules **IN** (High specificity means a positive result reliably confirms the disease). * **Screening vs. Diagnosis:** Screening tests should have high **Sensitivity** (to catch all cases), while confirmatory/diagnostic tests should have high **Specificity** (to avoid false labeling). * Specificity is independent of the prevalence of the disease in the population, unlike Predictive Values.

Q: Cronbach alpha is a measure of?

Internal consistency. **Explanation:** **Cronbach’s Alpha** is a statistical coefficient used to measure **Internal Consistency**, which is a specific type of **Reliability**. In medical research and psychometrics, when a questionnaire or scale (e.g., a depression screening tool) uses multiple items to measure the same underlying construct, Cronbach’s alpha determines how closely related those items are as a group. A value of $\geq 0.7$ is generally considered acceptable, indicating that the items consistently measure the same concept. **Analysis of Incorrect Options:** * **B. Content Validity:** This refers to how well a test measures every element of a construct (e.g., does a surgery exam cover all surgical topics?). It is usually assessed by expert panels, not by a single statistical coefficient like Cronbach’s alpha. * **C. Central Tendency:** These are descriptive statistics (Mean, Median, Mode) that identify the center of a data distribution. * **D. Standard Deviation:** This is a measure of **dispersion** or variability, indicating how much individual data points deviate from the mean. **High-Yield Pearls for NEET-PG:** * **Reliability vs. Validity:** Reliability is about **consistency** (reproducibility), while Validity is about **accuracy** (truthfulness). * **Split-half Reliability:** Another method to check internal consistency by splitting the test items into two halves and correlating them. * **Range:** Cronbach’s alpha ranges from 0 to 1. A value of 1 indicates perfect internal consistency, while 0 indicates none. * **Sensitivity/Specificity:** These are measures of **Validity** for diagnostic tests, whereas Cronbach’s alpha is a measure of **Reliability** for scales/surveys.

Question 1

A village is divided into five relevant subgroups for the purpose of a survey. Individuals from each subgroup are then selected randomly. What is this type of sampling called?

Accepted Answer

Stratified sampling

Answer

Simple Random sampling

Answer

Cluster Sampling

Answer

Systematic Sampling

Question 2

A chi-square test would be most appropriate for testing which one of the following hypotheses?

Accepted Answer

That a smaller proportion of people who were immunized against chickenpox subsequently develop zoster than those who were not immunized.

Answer

That the mean score of students is greater than that of other students.

Answer

That the mean blood pressure of black and white male-hypertensive patients taking ACE inhibitors is the same as that of black and white female-hypertensive patients taking ACE inhibitors and that of black and white males and females taking diuretics and placebos.

Answer

That the mean cost of treating a patient with coronary artery disease with angioplasty is greater than the mean cost of providing medical treatment.

Question 3

What is true about the standard normal distribution?

Accepted Answer

The total area under the curve is equal to 1.

Answer

The mean is equal to 1.

Answer

The mean is greater than the median, which is greater than the mode.

Answer

The distribution has a tail towards the right.

Question 4

Which of the following is true about a cohort study?

Accepted Answer

Incidence can be calculated

Answer

It proceeds from effect to cause

Answer

It is inexpensive

Answer

It requires a shorter time than a case-control study

Question 5

Interpret the statistical graph shown below:

Accepted Answer

Positive correlation

Answer

Negative correlation

Answer

Absent correlation

Answer

Spurious correlation

Question 6

If one variable is given, how can another variable be predicted?

Accepted Answer

Coefficient of regression

Answer

Coefficient of variation

Answer

Coefficient of correlation

Answer

Coefficient of determination

Question 7

What is the direction of a case-control study in relation to the direction of time?

Accepted Answer

The direction of the study is retrospective, but the direction of time is prospective.

Answer

The direction of the study is prospective, and the direction of time is also prospective.

Answer

The direction of the study is prospective, and the direction of time is retrospective.

Answer

The direction of the study is retrospective, and the direction of time is also retrospective.

Question 8

Regarding the normal curve, which of the following statements is/are true?

Accepted Answer

Both limbs of the curve touch the baseline

Answer

Curve is bilaterally symmetrical

Answer

There is a skew to the right

Answer

Mean, Median, Mode coincide

Question 9

A diagnostic test was performed on 150 individuals. The results are presented in the table below:

| Test Result | Disease Present | Disease Absent |
|---|---|---|
| Positive Test | 40 | 5 |
| Negative Test | 10 | 95 |

What is the specificity of this test?

Accepted Answer

0.95

Answer

0.05

Answer

0.4

Answer

0.8

Question 10

Cronbach alpha is a measure of?

Accepted Answer

Internal consistency

Answer

Content validity

Answer

Central tendency

Answer

Standard deviation

Biostatistics — MCQs

Biostatistics — MCQs

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