Biostatistics Practice Questions

Q: Calculate the relative risk for the given situation: | | Developed Malaria | Did Not Develop Malaria | Total | |---|:---:|:---:|:---:| | **Vaccinated** | 6 | 94 | 100 | | **Non-vaccinated** | 12 | 88 | 100 |

0.5. ***Correct: 0.5*** **Relative Risk (RR)** is calculated as: RR = Risk in exposed group / Risk in unexposed group **Step-by-step calculation:** - Risk in **vaccinated group** = 6/100 = 0.06 - Risk in **non-vaccinated group** = 12/100 = 0.12 - **RR = 0.06 / 0.12 = 0.5** **Interpretation:** An RR of **0.5 indicates a protective effect** of vaccination. Vaccinated individuals have **half the risk** (50% reduced risk) of developing malaria compared to non-vaccinated individuals. *Incorrect: 2* This is the **inverse** of the correct RR, calculated as 0.12/0.06 = 2 (risk in non-vaccinated / risk in vaccinated). This would incorrectly suggest vaccination **doubles the risk** of malaria, which contradicts the data showing vaccination is protective. *Incorrect: 1.5* This value does not result from the correct RR formula using the given incidence rates (0.06 vs 0.12). This may arise from incorrect formula application or confusion with other epidemiological measures like the **Odds Ratio**. *Incorrect: 1.7* This is not the result of standard RR calculation based on the incidence rates of 0.06 and 0.12. It represents a **calculation error** and has no epidemiological meaning in this context.

Q: The urban area of Delhi has 4000 people with different religions. Research is being done to study the dietary habits of the population. Which of the following techniques can be used to obtain a study sample?

Stratified random sampling. ***Stratified random sampling.***- This technique divides the population (Delhi area) into homogeneous subgroups (strata) based on the defining characteristic, which in this case is **religion**, to ensure proportional representation. - Since dietary habits are likely to vary significantly across different religious groups, stratification ensures that the study sample accurately reflects the **dietary heterogeneity** of the urban area. *Cluster random sampling*- **Cluster sampling** is typically used when the population is large and geographically dispersed; the basic unit sampled is a group (cluster), not the individual.- Selecting entire geographical clusters might not capture the full diversity of religious dietary habits, potentially leading to increased **sampling error**. *Simple random sampling*- **Simple random sampling** selects individuals purely randomly, irrespective of their subgroup (religious) membership.- This method risks selecting an inadequate number of individuals from smaller religious groups, thereby failing to accurately represent the **dietary practices** of the entire population. *Systematic random sampling*- **Systematic sampling** involves selecting every 'n'th member from a list and is logistically simple, but it does not account for the intrinsic heterogeneity (religion) of the population.- If the initial list is arranged in a pattern related to religious groups, this method could introduce a **hidden bias**, compromising the representativeness of the sample.

Q: Which of the following is the correct order of steps for conducting a research study? 1. Define the problem/hypothesis 2. Design the study methodology 3. Data collection and execution 4. Data analysis and interpretation

1,2,3,4. **1,2,3,4** - The correct research process begins with **defining the problem or hypothesis (1)**, which sets the foundation and direction for the entire study. - This is sequentially followed by **designing the study methodology (2)**, actual **data collection and execution (3)**, and finally, **data analysis and interpretation (4)**. *1,3,2,4* - Although starting correctly with **defining the research question (1)**, this sequence erroneously jumps to **data collection (3)** before finalizing the **study design (2)**. - Proper research requires the protocol, inclusion criteria, and sample size calculations (all part of **design 2**) to be complete prior to implementation. *2,1,4,3* - This sequence is illogical because it requires designing the study (**step 2**) before knowing what the study aims to achieve (**research question/step 1**). - Furthermore, **data analysis (4)** cannot proceed before all the necessary **data collection (3)** has been performed. *4,3,2,1* - This sequence is the complete reverse of scientific methodology, starting with the final step of **data interpretation and analysis (4)**. - A research study must always originate from a defined **research question (1)** and detailed planning, making this proposed order incorrect.

Q: In a Primary Health Centre (PHC), a study was done on diabetic patients. Mean weight was recorded before and after 6 months of dietary intervention. Which statistical test should be used to determine significance?

Paired t-test. ***Paired t-test*** - This test is appropriate for comparing the means of **two related samples** or measurements taken from the **same subjects** at two different time points (before and after intervention). - The study involves recording the mean weight of the *same* diabetic patients before and after a 6-month dietary intervention, making the samples dependent (paired). *Unpaired t-test* - The unpaired t-test (or Student's t-test) is used to compare the means of **two independent (unrelated) groups** (e.g., comparing the mean weight of patients in Group A vs. Group B). - It is unsuitable here because the measurements are taken from the same set of individuals, meaning the data points are related, not independent. *ANOVA* - **Analysis of Variance (ANOVA)** is used to compare the means of **three or more** independent groups (e.g., comparing mean weight across three different regions). - It is used when there are multiple levels of a factor or multiple independent variables, which is not the case when comparing two time points. *Chi-square test* - The Chi-square test is primarily used to analyze **categorical data** (frequencies or proportions) to determine if there is a significant association between two variables (e.g., relationship between gender and diabetes status). - It is unsuitable for comparing numerical values like mean weight measurements, which are continuous data.

Q: Which of the following is incorrectly matched with respect to the statistical parameter?

Mean, median - Dispersion. ***Mean, median - Dispersion*** - This statement is **incorrect** because the **mean** and **median** are measures of **central tendency** (location) of a distribution, not dispersion. - Measures of dispersion quantify the spread of data, such as **standard deviation**, range, and interquartile range. ***Standard error - Variation*** - **Standard error** is a measure of the **variation** (or dispersion) of sample means around the true population mean, making this a correct match. - Specifically, it estimates how much the sample mean is likely to deviate from the population mean. ***Correlation coefficient - Relationship*** - The **correlation coefficient** (e.g., Pearson's r) measures the **strength and direction of the linear relationship** between two variables, making this a correct match. - Its value ranges from -1 (perfect negative relationship) to +1 (perfect positive relationship). ***Moments - Skewness*** - **Moments** are specific mathematical calculations used to describe the shape and characteristics of a distribution; the **third moment** is specifically used to calculate **skewness**. - **Skewness** describes the asymmetry of the distribution (whether it leans left or right), and the third moment helps quantify this.

Q: In statistics, centiles and quartiles are considered as:

Measures of location/position. ***Measures of location/position***- Centiles (or **percentiles**) and **quartiles** are statistics that divide the data distribution into equal parts, indicating where a particular value stands relative to the rest of the data.- They are also known as **quantiles**, used to describe the location of specific data points within the distribution rather than summarizing the center or spread.*Measures of central tendency*- These statistics aim to describe the typical or **central value** of a dataset (e.g., **Mean**, **Median**, **Mode**).- While the median is technically the second quartile (**Q2**) and the 50th centile, the classifications of centiles and quartiles collectively are broader—measures of position.*Measures of dispersion*- These measures quantify the **spread** or **variability** of the data around the central value (e.g., **Standard Deviation**, **Variance**, Range).- Although quartiles are essential for calculating the **Interquartile Range (IQR)**, which is a measure of dispersion, the quartiles themselves define points of position.*Measures of correlation*- Correlation measures describe the **linear relationship** or association between **two variables** (e.g., Correlation Coefficient, R-value).- They are used in bivariate analysis and have no role in describing the position or central value of a single dataset.

Q: In a study done in a hospital, patients were categorized into three groups based on disease prevalence (Low, Medium, High), and individuals were then randomly selected from each group. What type of sampling is this?

Stratified random sampling. ***Correct: Stratified random sampling*** - This method involves dividing the population into non-overlapping subgroups (**strata**) based on a characteristic (here, disease prevalence: Low, Medium, High). - Subsequently, a **simple random sample** is drawn from *each* stratum independently to ensure representation from all groups. - This ensures that each subgroup is adequately represented in the final sample, making it ideal when the population has distinct subgroups. *Incorrect: Simple random sampling* - Every individual in the entire population has an equal and independent chance of being selected. - It does not involve dividing the population into specific subgroups or categories before selection. - This method may underrepresent or overrepresent certain subgroups by chance. *Incorrect: Systematic random sampling* - This involves selecting every *k*th element after a random start point, where *k* is the sampling interval (Population Size/Sample Size). - Like simple random sampling, it does not involve creating predefined strata based on characteristics like disease prevalence. - It's a simpler alternative to simple random sampling but doesn't ensure representation of specific subgroups. *Incorrect: Cluster random sampling* - The population is divided into natural groupings (**clusters**), such as geographical areas or schools. - Unlike stratification, entire clusters are randomly selected, and *all* individuals within the selected clusters (or a random sample thereof) are included in the study. - This differs from stratified sampling where we sample from ALL strata; in cluster sampling, we sample only SOME clusters.

Q: In a given population: - less than 15 years: 6000 - 15 to 64 years: 12000 - 65 years and above: 2000 Calculate the dependency ratio.

66 %. ***66 %*** - The **Dependency Ratio** measures the ratio of the economically dependent population to the economically productive population, usually expressed as a percentage. - **Dependent Population** (aged < 15 and ≥ 65): 6000 + 2000 = **8000** - **Productive Population** (aged 15-64): **12000** - **Dependency Ratio**: (8000 / 12000) × 100 = **66.67%** (rounded to 66%) *Incorrect: 33 %* - This figure is significantly lower than the true ratio and results from calculating the ratio of the dependent population to the **total population**, which is not the standard definition of the Dependency Ratio. - 33.3% represents the dependent population (8000) as a proportion of the total population (20000), not the dependency burden on the working population. *Incorrect: 50 %* - This result is obtained if only the young dependent group is used in the numerator (Young Dependency Ratio = 6000 / 12000 = **50%**). - However, the total Dependency Ratio must account for **both young and old dependents** to accurately reflect the economic burden. *Incorrect: 75 %* - Obtaining 75% would require the dependent population to be 9000 (i.e., 9000 / 12000), which is higher than the actual 8000 dependents. - This option represents an overestimation of the dependent burden on the working population.

Q: A new community intervention is initiated to reduce perinatal sepsis. Researchers allocate 20 Primary Health Centres (PHCs) to receive standard care and 20 PHCs to receive a community-based intervention. What type of study design is this?

Cluster-randomized control trial. ***Cluster-randomized control trial*** - A **Cluster-randomized control trial (C-RCT)** involves randomizing groups of individuals (clusters), such as entire PHCs or communities, rather than individual participants, to intervention or control arms. - Since whole **groups (20 PHCs)** are allocated to standard care or the intervention, it fits the definition of a C-RCT, which is often essential when an intervention cannot be delivered individually due to its nature (e.g., community-based programs). *Quasi-experimental study* - This design involves an intervention but lacks true **randomization** of participants or clusters, or it lacks a control group. - While both include control and intervention groups, the described scenario implies randomization (allocation), which makes a C-RCT a more specific and accurate fit than a general quasi-experimental design. *Cross-sectional study* - This design measures exposure and outcome simultaneously at a single point in time to determine **prevalence**. - It does not involve tracking groups over time or applying an **intervention**, which are key components of the described scenario. *Case-control study* - This is an observational study where individuals with a disease (cases) are compared to individuals without the disease (controls) to determine prior **exposure**. - This design is retrospective and does not involve the prospective application of a new **community intervention** as described in the question.

Q: Which of the following is the correct sequence of steps in a Randomized Controlled Trial (RCT)?

Randomisation → Manipulation → Follow-up → Assessment. **Randomisation → Manipulation → Follow-up → Assessment** is the correct sequence for conducting a Randomized Controlled Trial (RCT). - **Randomisation** is the essential first step that ensures baseline comparability between intervention and control groups, eliminating selection bias - **Manipulation** (intervention/treatment application) follows randomization - **Follow-up** involves monitoring participants over the study period - **Assessment** (outcome measurement) is performed at the end to evaluate the intervention's effect *Follow-up → Manipulation → Assessment → Randomisation* - Incorrect because randomization must occur before any intervention is applied - Starting with follow-up contradicts the fundamental RCT design *Manipulation → Assessment → Follow-up → Randomisation* - Fundamentally flawed as applying intervention before randomization introduces selection bias - This violates the core principle of RCTs (random allocation must precede intervention) *Assessment → Randomisation → Follow-up → Manipulation* - Incorrect sequence as assessment (outcome measurement) is the final stage, not the first - Manipulation must follow randomization, not come after follow-up

Question 1

Calculate the relative risk for the given situation:

| | Developed Malaria | Did Not Develop Malaria | Total |
|---|:---:|:---:|:---:|
| **Vaccinated** | 6 | 94 | 100 |
| **Non-vaccinated** | 12 | 88 | 100 |

Accepted Answer

0.5

Answer

1.5

Answer

2

Answer

1.7

Question 2

The urban area of Delhi has 4000 people with different religions. Research is being done to study the dietary habits of the population. Which of the following techniques can be used to obtain a study sample?

Accepted Answer

Stratified random sampling

Answer

Simple random sampling

Answer

Systematic random sampling

Answer

Cluster random sampling

Question 3

Which of the following is the correct order of steps for conducting a research study?
1. Define the problem/hypothesis
2. Design the study methodology
3. Data collection and execution
4. Data analysis and interpretation

Accepted Answer

1,2,3,4

Answer

1,3,2,4

Answer

2,1,4,3

Answer

4,3,2,1

Question 4

In a Primary Health Centre (PHC), a study was done on diabetic patients. Mean weight was recorded before and after 6 months of dietary intervention. Which statistical test should be used to determine significance?

Accepted Answer

Paired t-test

Answer

Chi-square test

Answer

Unpaired t-test

Answer

ANOVA

Question 5

Which of the following is incorrectly matched with respect to the statistical parameter?

Accepted Answer

Mean, median - Dispersion

Answer

Moments - Skewness

Answer

Standard error - Variation

Answer

Correlation coefficient - Relationship

Question 6

In statistics, centiles and quartiles are considered as:

Accepted Answer

Measures of location/position

Answer

Measures of dispersion

Answer

Measures of central tendency

Answer

Measures of correlation

Question 7

In a study done in a hospital, patients were categorized into three groups based on disease prevalence (Low, Medium, High), and individuals were then randomly selected from each group. What type of sampling is this?

Accepted Answer

Stratified random sampling

Answer

Systematic random sampling

Answer

Cluster random sampling

Answer

Simple random sampling

Question 8

In a given population:
- less than 15 years: 6000
- 15 to 64 years: 12000
- 65 years and above: 2000

Calculate the dependency ratio.

Accepted Answer

66 %

Answer

50 %

Answer

75 %

Answer

33 %

Question 9

A new community intervention is initiated to reduce perinatal sepsis. Researchers allocate 20 Primary Health Centres (PHCs) to receive standard care and 20 PHCs to receive a community-based intervention. What type of study design is this?

Accepted Answer

Cluster-randomized control trial

Answer

Cross-sectional study

Answer

Case-control study

Answer

Quasi-experimental study

Question 10

Which of the following is the correct sequence of steps in a Randomized Controlled Trial (RCT)?

Accepted Answer

Randomisation → Manipulation → Follow-up → Assessment

Answer

Follow-up → Manipulation → Assessment → Randomisation

Answer

Manipulation → Assessment → Follow-up → Randomisation

Answer

Assessment → Randomisation → Follow-up → Manipulation

Biostatistics — MCQs

Biostatistics — MCQs

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