Biostatistics Practice Questions

Q: For a group of 250 subjects, what value represents the 40th percentile?

100. **Explanation:** **1. Why the Correct Answer is Right:** In biostatistics, a **percentile** is a measure used to indicate the value below which a given percentage of observations in a group of observations falls. To calculate the position of a specific percentile in a dataset, the formula used is: * **Rank (n) = (P / 100) × N** * *P* = Percentile (40) * *N* = Total number of subjects (250) Applying the formula: $(40 / 100) \times 250 = 0.4 \times 250 = \mathbf{100}$. Therefore, the 100th value in the ordered dataset represents the 40th percentile. **2. Why Incorrect Options are Wrong:** * **Option A (7):** This is a random low number and does not correspond to any standard statistical calculation for this dataset. * **Option B (40):** This is a common distractor where students confuse the *percentile rank* (40th) with the *absolute value* (100). 40 is the percentage, not the count of subjects. * **Option D (140):** This value is mathematically incorrect. It might be reached if a student incorrectly adds the percentile to the total or miscalculates the percentage. **3. NEET-PG High-Yield Clinical Pearls:** * **Median:** The 50th percentile is always the Median. In this dataset, the median would be the 125th value. * **Quartiles:** The 25th percentile is the 1st Quartile (Q1), and the 75th percentile is the 3rd Quartile (Q3). * **Interquartile Range (IQR):** Calculated as Q3 – Q1; it contains the middle 50% of the data and is used to describe skewed distributions. * **Growth Charts:** In clinical practice, percentiles are most commonly used in pediatric growth charts (e.g., a child at the 95th percentile for weight is heavier than 95% of children their age).

Q: What was the sex ratio as per the 2011 census?

940. **Explanation:** The **Sex Ratio** is a critical demographic indicator in Biostatistics and Public Health, defined as the number of females per 1,000 males in a population. According to the **2011 Census of India**, the national sex ratio was recorded as **943** (often rounded to **940** in standard medical examinations like NEET-PG). This represented a slight improvement from the 2001 census figure of 933. **Analysis of Options:** * **Option B (940) - Correct:** As per official 2011 Census data, the sex ratio is 943. In multiple-choice questions, 940 is the most frequently cited "best fit" answer. * **Option A (970):** This value is incorrect for the national average. However, it is closer to the sex ratio of specific states with better gender parity (e.g., Tamil Nadu at 996). * **Option C (921):** This figure does not correspond to the 2011 national sex ratio. For context, the 1991 census recorded a low of 927. * **Option D (915):** This is often confused with the **Child Sex Ratio (0–6 years)**, which was **919** (often rounded to 914 or 915 in older texts) in the 2011 census—a declining trend that remains a major public health concern. **High-Yield Pearls for NEET-PG:** * **Highest Sex Ratio (State):** Kerala (1084). * **Lowest Sex Ratio (State):** Haryana (879). * **Highest Sex Ratio (UT):** Puducherry (1037). * **Lowest Sex Ratio (UT):** Daman & Diu (618). * **Definition:** In India, Sex Ratio is **Females/1000 Males**. (Note: Internationally, it is often expressed as Males/100 Females). * **NFHS-5 Data:** Recent surveys (2019-21) suggest a shift to 1020, but for "Census" specific questions, 2011 data (943/940) remains the gold standard.

Q: What is the best method to show the trend of events with the passage of time?

Line diagram. ### Explanation **1. Why Line Diagram is the Correct Answer:** A **Line Diagram** (or Line Graph) is the gold standard for representing **time-series data**. In biostatistics, it is used to show the "trend" of a variable over a continuous period (e.g., years, months, or weeks). By connecting discrete data points with a line, it allows the observer to immediately identify whether a phenomenon—such as the incidence of a disease or birth rates—is increasing, decreasing, or remaining stable over time. **2. Why Other Options are Incorrect:** * **Bar Diagram:** These are used for **discrete (qualitative)** data to compare different categories (e.g., number of hospital beds in different departments). They do not show continuity or trends effectively. * **Histogram:** This is used for **continuous quantitative** data to show frequency distribution (e.g., age distribution of a population). Unlike a line diagram, it represents a "snapshot" of data rather than a progression over time. * **Pie Chart:** This is used to show the **proportional segment** of a whole at a single point in time (e.g., causes of maternal mortality). It cannot depict changes over time. **3. High-Yield Clinical Pearls for NEET-PG:** * **Frequency Polygon:** If you join the midpoints of the bars of a histogram, you get a frequency polygon. It is used to compare two or more frequency distributions. * **Scatter Diagram:** Used to show the **correlation** (relationship) between two continuous variables (e.g., Height vs. Weight). * **Ogive (Cumulative Frequency Curve):** Used to determine the **median** of a distribution. * **Pictogram:** Uses small pictures or symbols to represent data; it is the easiest method for a layperson to understand.

Q: Which type of data measurement scale is represented by categories like 'happy', 'moderately happy', and 'very happy'?

Ordinal. ### Explanation The correct answer is **Ordinal**. **1. Why Ordinal is Correct:** The data measurement scale is determined by the relationship between the categories. In this case, 'happy', 'moderately happy', and 'very happy' represent qualitative categories that have a **natural, inherent order or rank**. While we know that 'very happy' is a higher state than 'moderately happy', the mathematical distance (interval) between these states is not quantifiable or equal. In biostatistics, any scale that ranks data without a fixed numerical distance is classified as an **Ordinal Scale**. **2. Why the Other Options are Incorrect:** * **Nominal:** This scale is used for naming categories without any specific order (e.g., Blood groups A, B, AB, O or Gender). Since 'happy' and 'very happy' have a clear hierarchy, they are not merely nominal. * **Interval:** This scale has a defined order and equal intervals between values, but **no absolute zero** (e.g., Temperature in Celsius). We cannot say 'very happy' is exactly "two units" happier than 'happy'. * **Ratio:** This is the highest level of measurement. It has equal intervals and a **true zero point** (e.g., Height, Weight, BP). Qualitative feelings like happiness cannot be measured on a ratio scale. **3. Clinical Pearls & High-Yield Facts for NEET-PG:** * **Mnemonic (NOIR):** **N**ominal < **O**rdinal < **I**nterval < **R**atio (from simplest to most complex). * **Likert Scales:** Most pain scales (Mild, Moderate, Severe) and patient satisfaction surveys are **Ordinal**. * **Statistical Test Selection:** For **Nominal/Ordinal** data, use **Non-parametric tests** (e.g., Chi-square, Mann-Whitney U). For **Interval/Ratio** data, use **Parametric tests** (e.g., t-test, ANOVA). * **Median** is the most appropriate measure of central tendency for Ordinal data.

Q: Which of the following is NOT a measure of central tendency?

Standard Deviation (SD). ### Explanation In biostatistics, data is summarized using two primary types of descriptive statistics: **Measures of Central Tendency** and **Measures of Dispersion**. **Why Standard Deviation (SD) is the correct answer:** Standard Deviation is a **Measure of Dispersion** (or variability). It quantifies how much the individual data points spread out or deviate from the mean. In medical research, a low SD indicates that the data points are close to the mean, while a high SD indicates a wide range of values (high variability). Since it measures "spread" rather than the "center," it is not a measure of central tendency. **Analysis of Incorrect Options:** * **Mean (Arithmetic Average):** The most common measure of central tendency. It is calculated by summing all observations and dividing by the total number. It is highly sensitive to extreme values (outliers). * **Median (Middle Value):** The value that divides a distribution into two equal halves when arranged in order. It is the preferred measure for skewed data as it is not affected by outliers. * **Mode (Most Frequent Value):** The value that occurs most frequently in a dataset. It is the only measure of central tendency that can be used for nominal (categorical) data. **High-Yield Clinical Pearls for NEET-PG:** * **Normal Distribution:** In a perfectly symmetrical bell-shaped curve, **Mean = Median = Mode**. * **Skewed Data:** In a **Positively Skewed** distribution (tail to the right), the order is **Mean > Median > Mode**. In a **Negatively Skewed** distribution (tail to the left), the order is **Mean < Median < Mode**. * **Measures of Dispersion:** Apart from SD, these include Range, Variance, and Mean Deviation. * **Standard Error (SE):** Often confused with SD; SE measures the precision of the sample mean compared to the true population mean ($SE = SD / \sqrt{n}$).

Q: What type of statistical test is ANOVA?

Parametric test. **Explanation:** **ANOVA (Analysis of Variance)** is a **parametric test** used to compare the means of three or more independent groups. It is considered parametric because it relies on specific assumptions about the population parameters, primarily that the data follows a **normal distribution** and exhibits **homogeneity of variance** (equal variance across groups). * **Why Option A is correct:** ANOVA evaluates the "variance" to determine if group means differ significantly. Since it requires interval or ratio scale data and assumes a bell-shaped distribution, it falls under the category of parametric statistics. * **Why Option B is incorrect:** Non-parametric tests (like the Kruskal-Wallis test) are "distribution-free" and used for skewed data or ordinal scales. They do not assume a normal distribution. * **Why Option C is incorrect:** Qualitative tests deal with non-numerical categories. ANOVA is a quantitative statistical method used to analyze continuous numerical data. **High-Yield Clinical Pearls for NEET-PG:** 1. **The Rule of 3:** Use a **Z-test** for 2 groups (sample >30), **T-test** for 2 groups (sample <30), and **ANOVA** for **3 or more groups**. 2. **F-Ratio:** The test statistic for ANOVA is the **F-test**. 3. **Non-parametric Counterpart:** If the data for 3+ groups is not normally distributed, the non-parametric alternative to ANOVA is the **Kruskal-Wallis H test**. 4. **One-way vs. Two-way:** One-way ANOVA involves one independent variable (e.g., comparing BP across three different drug groups), while Two-way ANOVA involves two independent variables.

Q: What percentage of data falls between the 1st and 4th pentile?

60%. ### Explanation **Concept of Pentiles:** In biostatistics, **pentiles** (or quintiles) are values that divide a dataset into **five equal parts**, each representing **20%** of the total population. * **1st Pentile (P1):** Marks the 20th percentile. * **2nd Pentile (P2):** Marks the 40th percentile. * **3rd Pentile (P3):** Marks the 60th percentile. * **4th Pentile (P4):** Marks the 80th percentile. **Why 60% is Correct:** The question asks for the data falling **between** the 1st and 4th pentile. * The 1st pentile is at the 20% mark. * The 4th pentile is at the 80% mark. * Calculation: $80\% - 20\% = 60\%$. This range covers the 2nd, 3rd, and 4th quintile groups (20% + 20% + 20%). **Analysis of Incorrect Options:** * **A. 20%:** This represents the data within a single pentile group (e.g., between the 1st and 2nd pentile). * **B. 40%:** This represents the data between two consecutive pentile markers (e.g., between the 1st and 3rd pentile). * **D. 80%:** This represents the total data up to the 4th pentile starting from zero, rather than the data *between* the 1st and 4th. **High-Yield Clinical Pearls for NEET-PG:** * **Quartiles:** Divide data into 4 parts (25% each). The Interquartile Range (IQR) is $Q3 - Q1$ (50% of data). * **Deciles:** Divide data into 10 parts (10% each). * **Percentiles:** Divide data into 100 parts (1% each). * **Median:** Equivalent to the 50th percentile, 5th decile, and 2nd quartile. * **Wealth Index:** In India, the National Family Health Survey (NFHS) uses **quintiles** to classify the economic status of the population.

Question 1

For a group of 250 subjects, what value represents the 40th percentile?

Accepted Answer

100

Answer

7

Answer

40

Answer

140

Question 2

What was the sex ratio as per the 2011 census?

Accepted Answer

940

Answer

970

Answer

921

Answer

915

Question 3

What is the best method to show the trend of events with the passage of time?

Accepted Answer

Line diagram

Answer

Bar diagram

Answer

Histogram

Answer

Pie chart

Question 4

A screening test for colon cancer was applied to 1000 individuals. The test was positive in 320 and negative in 680. Of those with a positive test, 60 actually had the disease. Of those with a negative test, 20 actually had the disease. Calculate the positive predictive value of the test.

Accepted Answer

81%

Answer

12%

Answer

75%

Answer

28%

Question 5

If the American Heart Association lowered the cut-off threshold for hypertension, what would be the effect on the properties of blood pressure assessment as a screening test?

Accepted Answer

The negative predictive value will rise

Answer

The false negative rate will rise

Answer

The positive predictive value will rise

Answer

The sensitivity will fall

Question 6

Which type of data measurement scale is represented by categories like 'happy', 'moderately happy', and 'very happy'?

Accepted Answer

Ordinal

Answer

Nominal

Answer

Ratio

Answer

Interval

Question 7

Which of the following is NOT a measure of central tendency?

Accepted Answer

Standard Deviation (SD)

Answer

Mean

Answer

Mode

Answer

Median

Question 8

Which of the following is NOT included under the Consumer Protection Act?

Accepted Answer

ESI hospitals not included

Answer

Passed in 1986

Answer

Decision within 3-6 months

Answer

Right to safety

Question 9

What type of statistical test is ANOVA?

Accepted Answer

Parametric test

Answer

Non-parametric test

Answer

Qualitative test

Answer

None of the above

Question 10

What percentage of data falls between the 1st and 4th pentile?

Accepted Answer

60%

Answer

20%

Answer

40%

Answer

80%

Biostatistics — MCQs

Biostatistics — MCQs

On this page

Practice by Chapter

Want unlimited practice?