Biostatistics Practice Questions

Q: You are posted in the Army Medical Corps. The company officer is briefing you over the depth of snow in Rohtang pass over the period of last one month. This diagram is called as:

Histogram. ***Correct: Histogram*** - A **histogram** is used to represent the frequency distribution of a **continuous variable** over different time intervals or class intervals - In this case, the **depth of snow** (continuous quantitative data) is measured over **one month period** at Rohtang pass - Histograms display data using adjacent rectangular bars where the **height represents frequency or magnitude** and the **width represents class intervals** (time periods) - This is the standard method for showing trends of continuous environmental data over time in epidemiology and biostatistics *Incorrect: Scatter diagram* - Scatter diagrams are used to show the **relationship between two continuous variables** (bivariate data) - They display individual data points on X-Y coordinates to assess correlation - Not appropriate here as we're tracking a single variable (snow depth) over time, not examining relationships between two variables *Incorrect: Pie chart* - Pie charts represent **proportions or percentages** of categorical data as sectors of a circle - Used when showing parts of a whole (e.g., distribution of diseases, budget allocation) - **Cannot be used for continuous time-series data** like snow depth measurements - Not suitable for showing trends over time *Incorrect: Pictogram* - Pictograms use **pictures or symbols** to represent data quantities - Primarily used for simple visual representation for lay audiences - Less precise and not standard for scientific/medical data presentation - Not the conventional method for recording meteorological or environmental continuous data

Q: The person on the upper part of the image is an IV drug abuser who is undergoing rehabilitation. The people shown are either sexual contacts or person with whom he had shared a needle. From those contacts further information leads to multiple such drug addicts in the community who had not sought medical services till now. This is an example of:

Snowball sampling. ***Snowball sampling*** - This method involves **identifying initial subjects** (e.g., the IV drug abuser in rehabilitation) and then asking them to identify others within their network who fit the study criteria. - It is particularly useful for reaching **hidden or hard-to-reach populations**, such as IV drug abusers or individuals involved in stigmatized behaviors, as seen in this scenario where subsequent contacts lead to more unreached individuals. *Cluster sampling* - This method involves dividing the population into **clusters** (e.g., geographic areas) and then randomly sampling entire clusters. - It is not applicable here as the sampling is based on personal connections, not pre-defined groups or locations. *Stratified cluster sampling* - This is a combination of stratified and cluster sampling, where the population is first divided into **strata**, and then clusters are randomly sampled from each stratum. - This method is more complex and typically used when there's a need to ensure representation from specific subgroups within clusters, which is not the primary technique described. *Convenience sampling* - This method involves selecting participants who are **readily available** or easiest to access. - While the initial contact might seem convenient, the extended chain of referrals to find more individuals goes beyond mere convenience and represents a deliberate effort to leverage existing social networks.

Q: This is a map of an urban slum in New Delhi. The medical officer of PHC notified the higher authorities on observing multiple cases of measles in 1-2 years age group. The authorities conducted a survey of vaccine coverage in the area in the manner shown below. Which sampling is depicted here?

Cluster sampling. ***Cluster sampling*** - The image shows **groups (clusters)** of houses (red houses within red circles) being selected, and then all units within those selected groups are included in the sample. - This method is typically used when the population is naturally divided into groups, such as geographical areas or blocks, making it **cost-effective** and practical, especially in large, dispersed populations like an urban slum. *Simple random sampling* - This method would involve **randomly selecting individual houses** from the entire slum without any pre-defined grouping, which is not depicted in the image. - Each house would have an **equal chance of being selected**, and sampling would not be restricted to specific clusters. *Systematic random sampling* - Involves selecting houses at a **fixed interval** (e.g., every 5th house) from a sorted list or along a defined path after a random starting point. - The image does not show a systematic selection process or an underlying order for sampling the houses. *Stratified random sampling* - This method involves **dividing the population into homogeneous subgroups** (strata) based on a characteristic (e.g., age, income level) and then drawing a random sample from each stratum. - While the map shows 'sections', these are not necessarily strata based on a relevant characteristic, and the sampling is not shown to be proportional or disproportional across these sections.

Q: A professor at AIIMS was asked to conduct a study on hazardous effects of cellphone use on health of urban Indians. He selected the study group in the fashion shown below. It indicates:

Cluster random sampling. **Cluster random sampling** - The image shows distinct **groups (clusters)** like "Reliance," "Airtel," and "Vodafone," from which entire clusters or randomly selected individuals from within certain clusters are chosen for the sample. - In this method, the **population is divided into clusters**, and then a random sample of these clusters is drawn. All units within the selected clusters (or a random selection of units within selected clusters) are included in the sample. - This is the sampling method depicted in the image. *Simple random sampling* - This method involves selecting subjects from the entire population **randomly and independently**, where each member has an equal chance of being selected. - The image illustrates pre-defined groups and selection from within and between them, which isn't characteristic of a single, undifferentiated pool for simple random selection. *Systematic random sampling* - This technique involves selecting every **k-th individual** from a list, after a random start. - The visual representation does not suggest a continuous list or a patterned, interval-based selection process. *Stratified random sampling* - In this method, the population is divided into **homogeneous subgroups (strata)** based on shared characteristics, and then a simple random sample is drawn from each stratum. - While there are groups (Reliance, Airtel, Vodafone), the selection process shown (selecting some individuals from one group, some from another, and possibly an entire smaller group from a larger one) does not strictly adhere to sampling proportionally from each stratum to ensure representation.

Q: The given image shows which kind of sampling?

Systematic random sampling. ***Systematic random sampling*** - The image illustrates **systematic random sampling** where participants are selected at regular intervals from a list, using a starting point chosen randomly. - For example, if we have 100 people and want to sample 10, we could pick every 10th person after a random start between 1 and 10. *Simple random sampling* - In **simple random sampling**, every individual in the population has an **equal chance** of being selected, like drawing names from a hat. - The image does not show a random selection of individuals from the entire pool without any specific pattern or interval. *Stratified random sampling* - **Stratified random sampling** involves dividing the population into **subgroups (strata)** based on shared characteristics, then taking a random sample from each stratum. - The image does not show any deliberate division of the population into distinct strata before sampling. *Cluster random sampling* - **Cluster random sampling** involves dividing the population into **clusters**, randomly selecting entire clusters, and then sampling all individuals within the chosen clusters. - The image does not depict the selection of entire pre-defined groups or clusters of individuals.

Q: In the following diagram which is correct?

Mean > median > mode. ***Mean > median > mode*** - The diagram illustrates a **positively skewed distribution** (right-skewed), where the tail extends to the right. - In a positively skewed distribution, the correct order is always: **Mode mode > mean* - This order describes a **negatively skewed (left-skewed) distribution**, where the tail extends to the left. - In a negatively skewed distribution: Mean mode > median* - While the mean is indeed greater than the mode in a positively skewed distribution, the **median always lies between the mode and mean**. - The correct relationship for positive skew is: Mode < **Median** < Mean (not Mode < Mean < Median). - This violates the fundamental property that median is the middle value in skewed distributions. *Mean = mode = median* - This equality holds only for a **symmetrical distribution**, such as a **normal distribution** (bell curve). - In symmetrical distributions, data is evenly distributed around the center point. - The diagram clearly shows an **asymmetrical, right-skewed distribution**, making this incorrect.

Q: What is the area under the curve between the earmarked points?

68.2%. ***68.2%*** - The image displays a **normal distribution curve**, with vertical lines likely representing standard deviations from the mean. - The "earmarked points" appear to be at **-1 standard deviation and +1 standard deviation** from the mean. The area between these points in a normal distribution is approximately **68.2%** (according to the empirical rule). - This represents the probability that a value falls within one standard deviation of the mean in a normal distribution. *95.4%* - This value represents the area between **-2 and +2 standard deviations** from the mean in a normal distribution. - The vertical lines in the image are closer to the **first standard deviation marks, not the second**. - This would be correct if the earmarked points were at ±2 standard deviations. *99.7%* - This value represents the area between **-3 and +3 standard deviations** from the mean in a normal distribution. - The vertical lines clearly **do not extend to three standard deviations** from the mean. - This represents nearly all values in a normal distribution. *50%* - This value would represent the area from the mean to one of the tails, or the area below or above the mean. - The **symmetrical placement of the two earmarked points** around the central peak (mean) indicates an area covering both sides, not just one half or a tail. - This does not represent the area between two symmetrical points around the mean.

Q: What is correct about the distribution curve shown below?

Positively skewed distribution. ***Positively skewed distribution*** - The curve shown is **skewed to the right** (positively skewed), meaning the tail of the distribution extends further to the right. - In a positively skewed distribution, the **mean is typically greater than the median**, which is greater than the mode. - There are more values clustered on the left side of the graph, with outliers extending to the right. - The relationship is: **Mode < Median < Mean** *Normal distribution* - A **normal distribution** (or Gaussian distribution) is symmetrical, forming a bell-shaped curve. - In such a distribution, the **mean, median, and mode are all equal** and located at the center of the curve. - There is no skewness in a normal distribution. *Negatively skewed distribution* - A **negatively skewed distribution** is skewed to the left, meaning the tail of the distribution extends further to the left. - In a negatively skewed distribution, the **mean is typically less than the median**, which is less than the mode. - There are more values clustered on the right side of the graph, with outliers extending to the left. - The relationship is: **Mean < Median < Mode** *Square wave distribution* - A **square wave distribution** is a periodic, non-sinusoidal waveform where the amplitude alternates regularly and instantaneously between two fixed values. - This type of distribution is **not represented by a continuous, curved shape** like the one shown and is not a standard probability distribution in biostatistics.

Q: The following plot comparing pharmacokinetics of different ibuprofen brands is called:

Spaghetti plot. ***Spaghetti plot*** - A **spaghetti plot** is characterized by multiple lines, each representing an individual's data across different time points or conditions, creating a visual resemblance to strands of spaghetti. This plot is ideal for visualizing **individual changes** and patterns in longitudinal data. - In pharmacokinetics, spaghetti plots are useful to compare the **drug concentration profiles** of different brands or formulations within individuals or across a group, showing individual variability. *Kaplan Meier plot* - A Kaplan-Meier plot (or survival curve) is used to estimate the **survival probability** over time for a group of individuals. - It displays a step-wise curve that decreases over time, representing the proportion of subjects **surviving** or remaining event-free, which is clearly not what is depicted in the image. *Funnel plot* - A **funnel plot** is a scatter plot used in meta-analyses to detect **publication bias** or small study effects. - It plots the study effect size against a measure of its precision (e.g., standard error), typically forming a triangular or funnel shape if no bias is present. *Forest plot* - A **forest plot** is a graphical display used in meta-analyses to illustrate the **results of individual studies** along with their pooled estimate. - Each study is represented by a square and a horizontal line indicating the effect size and its **confidence interval**, respectively.

Q: The following statistical diagram is called

Forest plot. ***Forest plot*** - A **forest plot** is a graphical display used primarily in **meta-analysis** to show the results of multiple studies comparing treatment effects. - It displays individual study effect sizes (as squares or points) with their **confidence intervals** (as horizontal lines), along with an overall pooled effect estimate (typically shown as a diamond). - The vertical line represents **no effect** (null hypothesis), and studies whose confidence intervals cross this line show non-significant results. - Forest plots allow quick visual assessment of consistency across studies and the overall effect magnitude. *Funnel plot* - A funnel plot is used to **detect publication bias** in meta-analyses by plotting study effect sizes against their precision (or sample size). - It typically shows a scatter plot with a triangular "funnel" shape, where smaller studies show more scatter and larger studies cluster at the top. - This is distinctly different from a forest plot, which displays confidence intervals horizontally. *Box and whisker plot* - A box and whisker plot represents the **distribution of numerical data** through quartiles, median, and outliers. - It shows the minimum, first quartile (Q1), median (Q2), third quartile (Q3), and maximum values in a box-and-whisker format. - It does not display multiple study results or confidence intervals. *Stem and leaf plot* - A stem and leaf plot is a **simple way to display quantitative data** by separating each data point into a "stem" (leading digit) and a "leaf" (trailing digit). - This method organizes small to moderately sized datasets and shows the actual data values while preserving their distribution shape. - It does not show comparative study results or confidence intervals.

Question 1

You are posted in the Army Medical Corps. The company officer is briefing you over the depth of snow in Rohtang pass over the period of last one month. This diagram is called as:

Accepted Answer

Histogram

Answer

Scatter diagram

Answer

Pie chart

Answer

Pictogram

Question 2

The person on the upper part of the image is an IV drug abuser who is undergoing rehabilitation. The people shown are either sexual contacts or person with whom he had shared a needle. From those contacts further information leads to multiple such drug addicts in the community who had not sought medical services till now. This is an example of:

Accepted Answer

Snowball sampling

Answer

Cluster sampling

Answer

Stratified cluster sampling

Answer

Convenience sampling

Question 3

This is a map of an urban slum in New Delhi. The medical officer of PHC notified the higher authorities on observing multiple cases of measles in 1-2 years age group. The authorities conducted a survey of vaccine coverage in the area in the manner shown below. Which sampling is depicted here?

Accepted Answer

Cluster sampling

Answer

Simple random sampling

Answer

Systematic random sampling

Answer

Stratified random sampling

Question 4

A professor at AIIMS was asked to conduct a study on hazardous effects of cellphone use on health of urban Indians. He selected the study group in the fashion shown below. It indicates:

Accepted Answer

Cluster random sampling

Answer

Simple random sampling

Answer

Systematic random sampling

Answer

Stratified random sampling

Question 5

The given image shows which kind of sampling?

Accepted Answer

Systematic random sampling

Answer

Simple random sampling

Answer

Stratified random sampling

Answer

Cluster random sampling

Question 6

In the following diagram which is correct?

Accepted Answer

Mean > median > mode

Answer

Median > mode > mean

Answer

Mean > mode > median

Answer

Mean = mode = median

Question 7

What is the area under the curve between the earmarked points?

Accepted Answer

68.2%

Answer

95.4%

Answer

99.7%

Answer

50%

Question 8

What is correct about the distribution curve shown below?

Accepted Answer

Positively skewed distribution

Answer

Normal distribution

Answer

Negatively skewed distribution

Answer

Square wave distribution

Question 9

The following plot comparing pharmacokinetics of different ibuprofen brands is called:

Accepted Answer

Spaghetti plot

Answer

Kaplan Meier plot

Answer

Funnel plot

Answer

Forest plot

Question 10

The following statistical diagram is called

Accepted Answer

Forest plot

Answer

Funnel plot

Answer

Box and whisker plot

Answer

Stem and leaf plot

Biostatistics — MCQs

Biostatistics — MCQs

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