Biostatistics Practice Questions

Q: A study reports patient satisfaction levels as 'Satisfied', 'Very satisfied', and 'Dissatisfied'. Which type of scale best represents these categories?

Ordinal. ### Explanation **Why Ordinal is Correct:** The data presented (Satisfied, Very satisfied, Dissatisfied) represents **Ordinal data**. In biostatistics, an ordinal scale is used when data can be categorized into distinct groups that have a **natural rank or inherent order**, but the mathematical distance between the categories is not uniform or measurable. In this study, "Very satisfied" is clearly higher than "Satisfied," which is higher than "Dissatisfied," but you cannot quantify exactly *how much* more satisfied one patient is compared to another. **Why Other Options are Incorrect:** * **Nominal:** This scale is for naming or labeling categories without any inherent order (e.g., Blood groups A, B, O; Gender; or Color of eyes). Since satisfaction levels have a logical hierarchy, they are not merely nominal. * **Interval:** This scale has a defined order and equal intervals between values, but **no true zero point** (e.g., Temperature in Celsius). Satisfaction levels do not have measurable, equal mathematical intervals. * **Ratio:** This is the highest level of measurement. It has all the properties of an interval scale plus a **true zero point** (e.g., Height, Weight, Blood Pressure). Satisfaction levels cannot be zero in a mathematical sense. **Clinical Pearls & High-Yield Facts for NEET-PG:** * **Mnemonic for Scales (Lowest to Highest Complexity):** **NOIR** (**N**ominal → **O**rdinal → **I**nterval → **R**atio). * **Likert Scales:** Most surveys using "Strongly Agree" to "Strongly Disagree" are classic examples of **Ordinal** data. * **Cancer Staging:** TNM staging or WHO functional grades are **Ordinal** scales. * **Qualitative vs. Quantitative:** Nominal and Ordinal are **Qualitative (Categorical)**, while Interval and Ratio are **Quantitative (Numerical)**. * **Central Tendency:** For Ordinal data, the **Median** is the most appropriate measure of central tendency.

Q: Amount of alcohol consumption amongst a group of alcoholics, before and after intervention, was recorded. What is the most appropriate statistical test to assess 'significant change' resulting from the intervention program?

Paired t-test. ### Explanation The core of this question lies in identifying the type of data and the relationship between the study groups. **1. Why Paired t-test is correct:** * **Type of Data:** "Amount of alcohol consumption" is a **quantitative (numerical/continuous)** variable (e.g., ml/day). * **Study Design:** The measurements are taken from the **same group** of individuals at two different points in time (**Before and After** intervention). These are "dependent" or "paired" observations. * **Purpose:** To compare the means of two related groups to determine if the intervention caused a statistically significant change, the **Paired t-test** is the standard parametric test used. **2. Why other options are incorrect:** * **Unpaired (Independent) t-test:** This is used to compare the means of two **independent** groups (e.g., comparing alcohol intake between Group A and Group B). * **Chi-square test:** This is used for **qualitative (categorical)** data to compare proportions (e.g., comparing the number of "drinkers" vs. "non-drinkers" in two groups). It cannot analyze the "amount" of consumption directly. * **McNemar test:** This is used for **paired qualitative** data. It would be appropriate if we were looking at a "Yes/No" change in addiction status before and after treatment, rather than the specific amount consumed. ### High-Yield Clinical Pearls for NEET-PG: * **Quantitative Data + 2 Groups:** * Paired (Before/After) $\rightarrow$ **Paired t-test** * Unpaired (Group A vs B) $\rightarrow$ **Unpaired t-test** * **Quantitative Data + >2 Groups:** Use **ANOVA**. * **Qualitative Data + 2 Groups:** * Unpaired $\rightarrow$ **Chi-square test** * Paired $\rightarrow$ **McNemar test** * **Non-parametric alternative:** If the data is not normally distributed, the non-parametric alternative to the Paired t-test is the **Wilcoxon Signed-Rank test**.

Q: The Hb level in healthy women has a mean of 13.5 g/dl and a standard deviation of 1.5 g/dl. What is the Z-score for a woman with an Hb level of 15.0 g/dl?

1.0. ### Explanation **Concept:** The **Z-score** (Standard Score) is a fundamental biostatistical tool used to determine how many standard deviations a specific observation is from the mean. It allows us to compare individual data points within a normal distribution. The formula for calculating the Z-score is: $$Z = \frac{X - \mu}{\sigma}$$ *Where:* * **X** = Individual value (15.0 g/dl) * **μ (Mean)** = Average value (13.5 g/dl) * **σ (Standard Deviation)** = 1.5 g/dl **Calculation:** $Z = \frac{15.0 - 13.5}{1.5} = \frac{1.5}{1.5} = \mathbf{1.0}$ A Z-score of +1.0 indicates that the woman's Hb level is exactly **one standard deviation above the mean**. --- ### Analysis of Options: * **Option D (1.0) is Correct:** As calculated above, the difference between the value and the mean equals exactly one unit of standard deviation. * **Option C (2.0) is Incorrect:** This would require an Hb level of 16.5 g/dl ($13.5 + [2 \times 1.5]$). * **Options A (9.0) and B (10.0) are Incorrect:** These represent extreme outliers. In a normal distribution, 99.7% of all values fall within a Z-score of ±3. A Z-score of 10 would be physiologically improbable in this context. --- ### High-Yield Clinical Pearls for NEET-PG: 1. **Normal Distribution (Gaussian Curve):** * 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. **Z-score of 0:** This means the individual's value is exactly equal to the mean. 3. **Standard Normal Distribution:** A specific normal distribution where the **Mean is 0** and the **Standard Deviation is 1**. 4. **Application:** Z-scores are clinically used in **WHO Growth Charts** (e.g., Weight-for-height Z-scores) to diagnose malnutrition (Wasting/Stunting).

Q: In a study, a new treatment resulted in 36 deaths or treatment failures out of a sample of 120. With an alternative treatment, 26 treatment failures were reported from a sample size of 130. How many patients should be treated with the first treatment to avert one death?

10. ### Explanation The question asks for the number of patients needed to be treated with the first treatment to avert one death, which is the definition of **Number Needed to Treat (NNT)**. **1. Calculation of the Correct Answer (B):** * **Event Rate in Group 1 (EER):** 36/120 = 0.3 (30%) * **Event Rate in Group 2 (CER):** 26/130 = 0.2 (20%) * **Absolute Risk Reduction (ARR):** This is the arithmetic difference between the two event rates. * ARR = |EER – CER| = |0.3 – 0.2| = **0.1** * **Number Needed to Treat (NNT):** This is the inverse of ARR. * NNT = 1 / ARR = 1 / 0.1 = **10** * Therefore, 10 patients must be treated with the first treatment to prevent one additional death compared to the second treatment. **2. Why other options are incorrect:** * **Option A (100):** This is a common calculation error where the decimal point is misplaced (1/0.01 instead of 1/0.1). * **Option C (250):** This value does not correlate with the mathematical relationship between the provided sample sizes and outcomes. * **Option D (160):** This might result from incorrectly adding the total number of failures (36+26) or misapplying the formula. **3. Clinical Pearls & High-Yield Facts for NEET-PG:** * **NNT Formula:** $1 / \text{Absolute Risk Reduction (ARR)}$. * **Interpretation:** The lower the NNT, the more effective the treatment. An NNT of 1 means every single patient treated benefits. * **Number Needed to Harm (NNH):** Calculated similarly ($1 / \text{Absolute Risk Increase}$), it indicates how many patients must be exposed to a risk factor to cause one adverse event. * **Relative Risk Reduction (RRR):** Unlike ARR, RRR does not account for the baseline risk and can often make a treatment's effect look more impressive than it is.

Q: A total of 5000 patients with glaucoma are identified and surveyed regarding family history of glaucoma. What is this study design called?

Case series report. ### Explanation **1. Why Case Series Report is Correct:** A **Case Series** is a descriptive study design that describes a group of individuals with a common characteristic (in this case, 5,000 patients with glaucoma). The study simply observes and describes the distribution of a variable (family history) within this specific group. * **Key Identifier:** There is **no comparison group** (no control group of people without glaucoma). Since the researcher is only looking at "cases" to identify patterns or generate hypotheses, it is a case series. **2. Why the Other Options are Incorrect:** * **B. Case-control study:** This requires two groups: Cases (with glaucoma) and Controls (without glaucoma). The study would then compare the frequency of family history between these two groups to calculate an Odds Ratio. * **C. Clinical trial:** This is an experimental study where an intervention (like a new drug) is applied to one group and compared against a placebo or standard treatment. * **D. Cohort study:** This starts with a group of exposed and unexposed individuals (e.g., those with and without family history) and follows them forward in time to see who develops glaucoma. It measures incidence and Relative Risk. **3. NEET-PG High-Yield Pearls:** * **Descriptive vs. Analytical:** Case reports and case series are *descriptive* (generate hypotheses). Case-control and cohort studies are *analytical* (test hypotheses). * **The "No Control" Rule:** If a question describes a large number of patients with a disease but mentions no comparison group, the answer is almost always a **Case Series**. * **Hierarchy of Evidence:** Case series are low on the evidence pyramid because they cannot prove a causal association due to the lack of a control group.

Q: The prevalence of diabetes mellitus in a population was found to be 10 percent. What is the probability that three people selected at random from the population have the disease?

0.001. ### Explanation **1. Understanding the Correct Answer (B: 0.001)** This question tests the application of the **Multiplication Rule of Probability** for independent events. * **Prevalence (P):** 10% or 0.1. This represents the probability that any single individual selected at random has diabetes. * **Independence:** Since the individuals are selected at random from a large population, the health status of one person does not influence the status of the next. * **Calculation:** To find the probability of multiple independent events occurring together (Person 1 AND Person 2 AND Person 3), we multiply their individual probabilities: * $0.1 \times 0.1 \times 0.1 = 0.001$ (or $10^{-3}$). **2. Analysis of Incorrect Options** * **Option A (0.003):** This is a common error where the student **adds** the probabilities ($0.1 + 0.1 + 0.1 = 0.3$) and misplaces the decimal, or confuses the multiplication rule with simple addition. * **Option C (0.03):** This represents $0.1 \times 0.3$, which has no mathematical basis in this scenario. * **Option D (0.01):** This is the probability of only **two** people having the disease ($0.1 \times 0.1$). **3. High-Yield Clinical Pearls for NEET-PG** * **Addition Rule:** Used for "Either/Or" scenarios (mutually exclusive events). E.g., Probability of being Blood Group A OR B. * **Multiplication Rule:** Used for "And" scenarios (independent events). E.g., Probability of two siblings both having an autosomal recessive disorder ($1/4 \times 1/4 = 1/16$). * **Prevalence vs. Incidence:** Remember that Prevalence = Incidence × Mean Duration of disease ($P = I \times D$). In this question, prevalence is used as the "pre-test probability" for random selection. * **Complementary Probability:** The probability of a person *not* having diabetes is $1 - 0.1 = 0.9$. The probability that *none* of the three have the disease would be $0.9^3 = 0.729$.

Q: Calculate the median from the following values: 1.9, 1.9, 1.9, 2.1, 2.4, 2.5, 2.5, 2.9?

2.25. ### Explanation **1. Understanding the Correct Answer (C: 2.25)** The **Median** is the middle-most value in a data set when arranged in ascending or descending order. It is a measure of central tendency that is less affected by extreme values (outliers) compared to the Mean. To calculate the median: * **Step 1: Arrange the data.** The values are already provided in ascending order: 1.9, 1.9, 1.9, 2.1, 2.4, 2.5, 2.5, 2.9. * **Step 2: Count the number of observations ($n$).** Here, $n = 8$. * **Step 3: Apply the formula.** Since $n$ is **even**, the median is the average of the two middle terms ($\frac{n}{2}$ and $\frac{n}{2} + 1$). * The 4th term is **2.1**. * The 5th term is **2.4**. * $\text{Median} = \frac{2.1 + 2.4}{2} = \frac{4.5}{2} = \mathbf{2.25}$. **2. Analysis of Incorrect Options** * **A (1.2):** This value is not present in the data set and lacks mathematical relevance to the calculation. * **B (1.9):** This is the **Mode** (the most frequently occurring value), not the median. * **D (2.5):** This is the 6th and 7th term; selecting this ignores the rule for calculating the average of the two central points in an even-numbered data set. **3. Clinical Pearls & High-Yield Facts for NEET-PG** * **Best Measure of Central Tendency:** For **skewed data** (e.g., incubation periods, income), the **Median** is the most appropriate measure. * **Nominal Data:** Use **Mode**. * **Ordinal Data:** Use **Median**. * **Interval/Ratio Data (Normal Distribution):** Use **Mean**. * **Relationship in Positive Skew:** Mean > Median > Mode. * **Relationship in Negative Skew:** Mode > Median > Mean. * **Note:** The Median corresponds to the **50th Percentile** and the **2nd Quartile ($Q_2$)**.

Question 1

What is a frequency curve?

Accepted Answer

When the number of observations is large and the group interval is reduced, a frequency polygon loses its angulations and becomes a curve.

Answer

It is a frequency polygon presenting variation by a line, showing the trend of an event over a period of time.

Answer

It is a graph of cumulative frequency distribution.

Answer

It is an area diagram of frequency distribution developed over a histogram.

Question 2

A study reports patient satisfaction levels as 'Satisfied', 'Very satisfied', and 'Dissatisfied'. Which type of scale best represents these categories?

Accepted Answer

Ordinal

Answer

Nominal

Answer

Interval

Answer

Ratio

Question 3

Amount of alcohol consumption amongst a group of alcoholics, before and after intervention, was recorded. What is the most appropriate statistical test to assess 'significant change' resulting from the intervention program?

Accepted Answer

Paired t-test

Answer

Unpaired t-test

Answer

Chi-square test

Answer

McNemar test

Question 4

The Hb level in healthy women has a mean of 13.5 g/dl and a standard deviation of 1.5 g/dl. What is the Z-score for a woman with an Hb level of 15.0 g/dl?

Accepted Answer

1.0

Answer

9.0

Answer

10.0

Answer

2.0

Question 5

In a study, a new treatment resulted in 36 deaths or treatment failures out of a sample of 120. With an alternative treatment, 26 treatment failures were reported from a sample size of 130. How many patients should be treated with the first treatment to avert one death?

Accepted Answer

10

Answer

100

Answer

250

Answer

160

Question 6

In a study evaluating the health hazards of a drug versus a placebo, the following results were obtained: Placebo group: 15225 people, 1605 affected. Drug group: 15225 people, 1804 affected. Which of the following is true regarding the risk reduction?

Accepted Answer

RRR 11%, ARR 1%

Answer

Relative risk reduction (RRR) is 11%, Absolute risk reduction (ARR) is 11%

Answer

RRR 1%, ARR 11%

Answer

RRR 1%, ARR 1%

Question 7

A total of 5000 patients with glaucoma are identified and surveyed regarding family history of glaucoma. What is this study design called?

Accepted Answer

Case series report

Answer

Case-control study

Answer

Clinical trial

Answer

Cohort study

Question 8

Confounding factors can be eliminated by all except:

Accepted Answer

Ethical consideration

Answer

Matching

Answer

Randomization

Answer

Stratification

Question 9

The prevalence of diabetes mellitus in a population was found to be 10 percent. What is the probability that three people selected at random from the population have the disease?

Accepted Answer

0.001

Answer

0.003

Answer

0.03

Answer

0.01

Question 10

Calculate the median from the following values: 1.9, 1.9, 1.9, 2.1, 2.4, 2.5, 2.5, 2.9?

Accepted Answer

2.25

Answer

1.2

Answer

1.9

Answer

2.5

Biostatistics — MCQs

Biostatistics — MCQs

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