Biostatistics Practice Questions

Q: Given a normal body temperature of 98.6 F with a standard deviation of 1 F, what is the lower limit of body temperature for 95% of persons?

96 F. ### Explanation This question tests your understanding of the **Normal Distribution (Gaussian Curve)**, a fundamental concept in biostatistics used to define "normal" biological ranges. **1. Why Option B is Correct:** In a normal distribution, the data is distributed around the mean ($\mu$) based on standard deviations ($\sigma$). The key property to remember is the **Empirical Rule**: * Mean ± 1 SD covers **68.3%** of the population. * Mean ± 2 SD covers **95.4%** (commonly simplified to 95%) of the population. * Mean ± 3 SD covers **99.7%** of the population. To find the range for 95% of the population, we use the formula: **Mean ± 2 SD**. * Upper Limit: $98.6 + (2 \times 1) = 100.6^\circ\text{F}$ * Lower Limit: $98.6 - (2 \times 1) = \mathbf{96.6^\circ\text{F}}$ Rounding to the nearest whole number provided in the options, **96°F** is the correct lower limit. **2. Why Other Options are Incorrect:** * **Option A (97°F):** This represents approximately Mean - 1 SD ($98.6 - 1 = 97.6$). This would only account for the lower limit of the 68% range. * **Option C (95°F) & Option D (94°F):** These values fall beyond the 2 SD range. 95.6°F would be the lower limit for 99.7% of the population (Mean - 3 SD). **3. High-Yield Clinical Pearls for NEET-PG:** * **Standard Normal Curve:** Has a mean of 0 and a variance/SD of 1. * **Confidence Interval (CI):** For a 95% CI, the precise multiplier is **1.96**, though "2" is frequently used in MCQ calculations for simplicity. * **Z-score:** Indicates how many standard deviations a value is from the mean. A Z-score of ±1.96 corresponds to the 95% confidence limits. * **Symmetry:** In a normal distribution, Mean = Median = Mode. If the curve is skewed, this equality is lost.

Q: In a set of data with highly variable values, what is the best measure of central tendency?

Median. **Explanation:** In biostatistics, the choice of central tendency depends on the distribution of the data. When a dataset contains **highly variable values** or **extreme outliers** (skewed distribution), the **Median** is the most robust measure. **1. Why Median is correct:** The Median is the middle-most value of a dataset when arranged in ascending or descending order. Unlike the Mean, the Median is **not affected by extreme values (outliers)**. In medical research, data like incubation periods, hospital stay duration, or income levels are often skewed; the Median provides a more "typical" representation of such data because it depends on the position of observations rather than their numerical magnitude. **2. Why other options are incorrect:** * **Mean (Arithmetic Average):** While it is the most commonly used measure, it is highly sensitive to outliers. A single extremely high value will pull the Mean toward it, making it unrepresentative of the "center" in skewed data. * **Mode:** This is the most frequently occurring value. It is often unstable and may not exist or may be far from the center in highly variable datasets. * **Standard Deviation:** This is a measure of **dispersion (spread)**, not central tendency. It describes how much the values deviate from the Mean. **High-Yield Clinical Pearls for NEET-PG:** * **Normal Distribution:** Mean = Median = Mode. * **Positively Skewed Data:** Mean > Median > Mode (Mean is pulled toward the tail). * **Negatively Skewed Data:** Mean < Median < Mode. * **Best measure for Nominal data:** Mode. * **Best measure for Ordinal/Skewed data:** Median.

Q: A study is designed to evaluate the relationship between smoking exposures during the postpartum period and the child's birth weight after delivery. What type of study is this?

Prospective cohort. ### Explanation **Why Prospective Cohort is Correct:** In this study design, the researcher starts with a group of individuals (postpartum mothers) who are currently exposed to a factor (smoking) and follows them over time to observe the development of an outcome (child’s weight/growth). * **Directionality:** It moves from **Cause (Exposure) to Effect (Outcome)**. * **Timing:** Since the exposure is measured *before* the outcome is fully assessed over the postpartum period, it is prospective. * **Key Concept:** Cohort studies are the gold standard for determining **Incidence** and **Relative Risk**. **Why Other Options are Incorrect:** * **A. Case-Control:** This would start with the outcome (e.g., children who already have low birth weight) and look *backwards* in time to see if their mothers smoked. It moves from Effect to Cause. * **C. Cross-sectional:** This provides a "snapshot" where exposure and outcome are measured at the same single point in time. it cannot establish a temporal relationship (which came first). * **D. Clinical Trial (RCT):** This involves an intervention. It would be unethical to intentionally assign mothers to a "smoking group" to see the effect on their children. **High-Yield Clinical Pearls for NEET-PG:** * **Cohort Study:** Best for rare exposures; can study multiple effects of a single exposure. * **Case-Control Study:** Best for rare diseases; uses **Odds Ratio** as the measure of association. * **Temporal Association:** The strongest criteria of Bradford Hill's criteria for causality, best demonstrated by prospective cohort studies. * **Recall Bias:** Common in Case-Control studies; **Selection Bias/Attrition** is more common in Cohort studies.

Q: What is a disadvantage of a case-control study when compared to a cohort study?

It cannot measure the cause-to-effect relationship.. ### Explanation **Why the correct answer is right:** The primary disadvantage of a **case-control study** is its inability to establish a definitive **temporal relationship** (cause-to-effect). In a case-control study, we start with the outcome (the disease) and look backward in time to identify exposures. Because both the exposure and the outcome have already occurred at the time the study begins, it is difficult to prove that the exposure preceded the disease. In contrast, a **cohort study** starts with a healthy population, identifies the exposure first, and follows them forward to see who develops the disease, making it the gold standard for establishing temporality and calculating **Incidence**. **Analysis of Incorrect Options:** * **A & B (Easy, Rapid, and Inexpensive):** These are actually **advantages** of case-control studies. Since they do not require long-term follow-up or large sample sizes, they are more resource-efficient than cohort studies. * **D (Useful in rare diseases):** This is another major **advantage**. Because you can specifically recruit "cases" of a rare condition, you don't have to wait years for the disease to manifest in a general population (as you would in a cohort study). **High-Yield NEET-PG Pearls:** * **Measure of Association:** Case-control studies use **Odds Ratio (OR)**; Cohort studies use **Relative Risk (RR)** and **Attributable Risk (AR)**. * **Directionality:** Case-control is **Retrospective** (Effect to Cause); Cohort is usually **Prospective** (Cause to Effect). * **Bias:** Case-control studies are highly prone to **Recall Bias** and **Selection Bias**. * **Incidence:** You **cannot** calculate Incidence from a case-control study; it can only be calculated from a cohort study.

Q: A case series report is a type of:

Observational study. ### Explanation **1. Why the Correct Answer is Right:** An **Observational study** is one where the investigator simply observes and records the natural course of events without any intervention or manipulation of the study subjects. A **Case Series** is a descriptive observational study that describes the characteristics of a group of patients with a common disease or exposure. Since the researcher is merely documenting clinical findings, outcomes, or unusual presentations in a group of patients without assigning a treatment or using a control group, it falls strictly under the umbrella of observational research. **2. Why the Other Options are Wrong:** * **Analytic study (A):** These studies (e.g., Case-Control, Cohort) are designed to test a hypothesis and determine the association between an exposure and an outcome using a **comparison group**. A case series lacks a control group, making it descriptive, not analytic. * **Experimental study (B) / Intervention study (D):** These terms are often used interchangeably (e.g., Randomized Controlled Trials). In these studies, the investigator actively **manipulates the exposure** (e.g., giving a drug) to observe the effect. In a case series, the "exposure" or "treatment" has already occurred or is happening naturally; the researcher does not control it. **3. NEET-PG High-Yield Pearls:** * **Hierarchy of Evidence:** Case series are higher in the hierarchy than Case Reports but lower than Case-Control and Cohort studies. * **Key Feature:** The hallmark of a Case Series is the **absence of a control group**. * **Usefulness:** They are the best study design for identifying **new/emerging diseases** or rare side effects (e.g., the first reports of Kaposi Sarcoma in HIV patients). * **Limitation:** They cannot be used to calculate "Relative Risk" or "Odds Ratio" because there is no comparison group.

Q: Which of the following statistical tests can be used to study ordinal data from two independent samples from a population that is not normally distributed?

The Wilcoxon rank-sum test. **Explanation:** The core of this question lies in identifying the correct **non-parametric test** for comparing two independent groups. **Why Option B is Correct:** The **Wilcoxon rank-sum test** (also known as the **Mann-Whitney U test**) is the non-parametric equivalent of the independent Student’s t-test. It is specifically used when: 1. The data is **ordinal** (ranked) or continuous but **not normally distributed**. 2. There are **two independent samples** (e.g., comparing pain scores between Group A and Group B). Since the question specifies non-normal distribution and ordinal data, this is the most appropriate choice. **Why Other Options are Incorrect:** * **A. Student’s t-test:** This is a **parametric test**. It requires the data to be continuous (interval/ratio scale) and follow a **normal distribution**. * **C. Chi-square test:** This test is used for **categorical (nominal) data** to compare proportions or test the association between two variables (e.g., Smoker vs. Non-smoker). * **D. One-way ANOVA:** This is a parametric test used to compare the means of **three or more** independent groups. Its non-parametric counterpart is the Kruskal-Wallis test. **High-Yield Clinical Pearls for NEET-PG:** * **Parametric vs. Non-Parametric:** If the data is "Normal," use Parametric. If "Skewed" or "Ordinal," use Non-Parametric. * **Wilcoxon Signed-Rank Test:** Do not confuse this with the Rank-Sum test. The *Signed-Rank* test is for **paired** data (e.g., before and after treatment in the same patient). * **Memory Aid:** **M**ann-Whitney **U** test = **U**npaired data; **W**ilcoxon **S**igned-rank = **S**ame person (Paired).

Q: In a cohort study, out of those exposed to a risk factor, 10 are diseased, and out of those not exposed to the risk factor, 5 are diseased. What is the relative risk?

2. ### Explanation **1. Understanding the Correct Answer (B: 2)** Relative Risk (RR), also known as Risk Ratio, is the primary measure of association in a **Cohort Study**. It compares the incidence of a disease among those exposed to a risk factor with the incidence among those not exposed. The formula for Relative Risk is: **RR = Incidence among exposed (Ie) / Incidence among non-exposed (Io)** In this question: * Incidence among exposed (Ie) = 10 * Incidence among non-exposed (Io) = 5 * **RR = 10 / 5 = 2** An RR of 2 indicates that the exposed group is twice as likely to develop the disease compared to the non-exposed group, suggesting a positive association between the risk factor and the disease. **2. Analysis of Incorrect Options** * **Option A (1.33):** This is a mathematical error, likely arising from incorrect division or adding values incorrectly. * **Option C (0.5):** This is the inverse (5/10). An RR < 1 indicates a protective effect (e.g., a vaccine), which contradicts the data provided. * **Option D (50):** This is a calculation error, possibly from multiplying the values instead of dividing them. **3. NEET-PG High-Yield Pearls** * **Study Design:** RR is calculated in **Prospective Cohort Studies**. It cannot be calculated in Case-Control studies (where Odds Ratio is used instead). * **Interpretation:** * RR = 1: No association. * RR > 1: Positive association (Risk factor). * RR < 1: Negative association (Protective factor). * **Attributable Risk (AR):** Calculated as (Ie - Io) / Ie × 100. It indicates the amount of disease that can be prevented if the exposure is eliminated. * **Incidence:** Cohort studies are the only way to directly calculate the incidence of a disease.

Q: Which of the following is true regarding random error?

Error in sampling. ### Explanation **Correct Answer: C. Error in sampling** **Understanding Random Error** In biostatistics, **Random Error** (also known as sampling error) occurs due to chance variations that happen when a sample is taken from a population. Even with a perfectly designed study, a sample may not perfectly represent the population simply due to "the luck of the draw." * **Key Characteristic:** It is unpredictable and non-systematic. * **Mitigation:** Random error can be reduced by **increasing the sample size** (which narrows the confidence interval and increases precision). **Analysis of Incorrect Options:** * **Option A (Systematic differences):** This describes **Selection Bias**. Bias is a systematic error that results in an incorrect estimate of the association between exposure and outcome. * **Option B (Questions about past history):** This refers to **Recall Bias**, a type of information/measurement bias common in case-control studies where cases tend to remember past events more clearly than controls. * **Option D (Different rates of admission):** This is a specific type of selection bias known as **Berkson’s Bias** (Admission Rate Bias), occurring when hospital-based samples do not represent the general population. **High-Yield Pearls for NEET-PG:** 1. **Random Error vs. Bias:** Random error affects **Precision** (reliability); Systematic error (Bias) affects **Validity** (accuracy). 2. **P-value:** The p-value is the probability that the observed result occurred due to random error (chance) alone. 3. **Sample Size:** Increasing sample size reduces random error but has **no effect** on systematic bias. 4. **Types of Bias:** Always remember that Bias is an error in design/conduction, whereas Random Error is an error in sampling.

Question 1

Given a normal body temperature of 98.6

F with a standard deviation of 1

F, what is the lower limit of body temperature for 95% of persons?

Accepted Answer

96

F

Answer

97

F

Answer

95

F

Answer

94

F

Question 2

In a town with a population of 20,000, there were 456 live births in a year. Of these, 56 resulted in stillbirths. The total number of deaths was 247, with 56 deaths occurring within the first 28 days of life and 34 deaths occurring after 28 days but before completing the first year of life. Calculate the Infant Mortality Rate for this area.

Accepted Answer

225

Answer

197

Answer

392

Answer

344

Question 3

In a set of data with highly variable values, what is the best measure of central tendency?

Accepted Answer

Median

Answer

Mean

Answer

Mode

Answer

Standard Deviation

Question 4

A study is designed to evaluate the relationship between smoking exposures during the postpartum period and the child's birth weight after delivery. What type of study is this?

Accepted Answer

Prospective cohort

Answer

Case control

Answer

Cross sectional

Answer

Clinical trial

Question 5

A cardiologist found a highly significant correlation coefficient (r = 0.90) between systolic blood pressure and serum cholesterol values of the patients attending his clinic. Which of the following statements is a wrong interpretation of the correlation coefficient observed?

Accepted Answer

Since there is a high correlation, the magnitude of both the measurements are likely to be close to each other.

Answer

A patient with a high level of systolic blood pressure is also likely to have a high level of serum cholesterol.

Answer

A patient with a low level of systolic blood pressure is also likely to have a low level of serum cholesterol.

Answer

About 80% of the variation in systolic blood pressure among his patients can be explained by their serum cholesterol values.

Question 6

What is a disadvantage of a case-control study when compared to a cohort study?

Accepted Answer

It cannot measure the cause-to-effect relationship.

Answer

It is easy to carry out.

Answer

It is rapid and inexpensive.

Answer

It is useful in rare diseases.

Question 7

A case series report is a type of:

Accepted Answer

Observational study

Answer

Analytic study

Answer

Experimental study

Answer

Intervention study

Question 8

Which of the following statistical tests can be used to study ordinal data from two independent samples from a population that is not normally distributed?

Accepted Answer

The Wilcoxon rank-sum test

Answer

The Student's t-test

Answer

The Chi-square test

Answer

The one-way analysis of variance

Question 9

In a cohort study, out of those exposed to a risk factor, 10 are diseased, and out of those not exposed to the risk factor, 5 are diseased. What is the relative risk?

Accepted Answer

2

Answer

1.33

Answer

0.5

Answer

50

Question 10

Which of the following is true regarding random error?

Accepted Answer

Error in sampling

Answer

Systematic differences in characteristic between cases and control

Answer

Cases and controls are asked questions about their past history

Answer

Different rates of admission in hospital

Biostatistics — MCQs

Biostatistics — MCQs

On this page

Practice by Chapter

Want unlimited practice?