Biostatistics Practice Questions

Q: The appropriate statistical test to find out obesity as a significant risk factor for breast cancer is:

Chi-square test. ***Chi-square test*** - The **chi-square test** is used to determine if there is a **significant association** between two **categorical variables**. - In this scenario, both obesity (yes/no) and breast cancer (yes/no) are categorical, making chi-square appropriate to assess if obesity is a risk factor. *Wilcoxon’s signed rank test* - This is a **non-parametric test** used for comparing two related samples or repeated measurements on a single sample, especially when data are not normally distributed. - It is not suitable for assessing the association between two independent categorical variables like obesity and breast cancer. *Student’s paired ‘t’ test* - The **paired t-test** is used to compare the means of two related groups or measurements from the same subject under different conditions (e.g., before and after an intervention). - This test is designed for **continuous data** and would not be appropriate for the categorical variables of obesity and breast cancer. *Student’s unpaired ‘t’ test* - The **unpaired t-test** (also known as independent samples t-test) is used to compare the means of two independent groups for a **continuous outcome variable**. - It is not suitable when both the exposure (obesity) and the outcome (breast cancer) are categorical variables.

Q: Which of the following is/are the measure(s) of dispersion? 1. Mode 2. Median 3. Standard Deviation Select the correct answer using the code given below:

3 only. ***Correct: 3 only*** - **Standard Deviation** is a direct measure of dispersion that quantifies the amount of variation or spread of data values around the mean - It indicates how much individual data points deviate from the average, making it a key statistic for understanding the **spread** within a dataset - Other common measures of dispersion include **range, variance, interquartile range, and coefficient of variation** *Incorrect: 1, 2 and 3* - **Mode** and **Median** are measures of **central tendency**, not dispersion - They describe the center or typical value of a dataset, not the spread or variability - While they provide insight into the data's distribution, they do not quantify how spread out the data points are *Incorrect: 2 and 3 only* - **Median** is a measure of **central tendency** representing the middle value when data is ordered, not a measure of dispersion - Only **Standard Deviation** from this option is a measure of dispersion, making this choice incorrect *Incorrect: 1 and 2 only* - Both **Mode** and **Median** are measures of **central tendency** - Mode indicates the most frequent value and Median represents the middle value - Neither provides information about how **spread out** or dispersed the data points are around the center

Q: Analytical studies include the following methods of studies except:

Cross sectional studies. ***Cross sectional studies*** - **Cross-sectional studies** are generally classified as **descriptive studies** as they assess the prevalence of a disease and/or risk factors at a single point in time, rather than analyzing cause-and-effect relationships. - While they can identify associations, they cannot establish **temporality** or causality between an exposure and an outcome, which is a hallmark of analytical studies. *Randomised controlled trials* - **Randomized controlled trials (RCTs)** are the gold standard for analytical studies, specifically for evaluating interventions, due to their ability to establish **causality** through random assignment and control groups. - They are prospective in nature and aim to assess the effect of an intervention on an outcome, controlling for confounding. *Cohort studies* - **Cohort studies** are a type of **observational analytical study** where a group of individuals exposed to a risk factor and a group not exposed are followed over time to compare disease incidence. - They are crucial for studying rare exposures and the natural history of diseases, allowing for the calculation of incidence rates and relative risks. *Case control studies* - **Case-control studies** are **retrospective analytical studies** that compare individuals with a disease (cases) to individuals without the disease (controls) and look back in time to identify past exposures. - These studies are efficient for investigating rare diseases and multiple exposures for a single outcome, allowing for the calculation of odds ratios.

Q: Which one of the following is not a measure of dispersion?

Mean. ***Mean*** - The **mean** is a measure of **central tendency**, representing the average value of a dataset. - It describes the typical value around which data points cluster, rather than how spread out they are. *Mean deviation* - **Mean deviation** is a measure of **dispersion** that calculates the average of the absolute differences between each data point and the mean of the dataset. - It quantifies the average deviation of data points from the center. *Standard deviation* - **Standard deviation** is a widely used measure of **dispersion** that indicates the average amount of variability or spread around the mean. - A higher standard deviation suggests data points are more spread out from the mean. *Range* - The **range** is a simple measure of **dispersion** calculated as the difference between the highest and lowest values in a dataset. - It provides a basic idea of the total spread of data from its extremes.

Q: The agreement (yes/no) between two observers is statistically measured by:

Kappa coefficient. **Kappa coefficient** - The **kappa coefficient** measures the **inter-rater agreement** for qualitative items, such as a "yes/no" decision, beyond what would be expected by chance. - It takes into account the observed agreement and the agreement expected by chance, providing a more robust measure of agreement than simple percentage agreement. *Correlation coefficient* - The **correlation coefficient** measures the **strength and direction of a linear relationship between two quantitative variables**, not the agreement between two observers on a categorical outcome. - It is used for continuous data and indicates how closely data points fit a linear regression line. *Sensitivity* - **Sensitivity** is a measure of a test's ability to correctly identify individuals who **have a disease (true positive rate)**. - It is not used to assess the agreement between two observers but rather the performance of a diagnostic test against a gold standard. *Specificity* - **Specificity** is a measure of a test's ability to correctly identify individuals who **do not have a disease (true negative rate)**. - Like sensitivity, it evaluates the performance of a diagnostic test and not the consistency of observations between two different raters.

Q: By which one of the following studies can relative risk be best calculated?

Cohort study. ***Cohort study*** - A cohort study directly follows groups of individuals (cohorts) over time to observe the **incidence of disease** in exposed versus unexposed groups. - This design allows for the direct calculation of **absolute risks** in each group, from which the **relative risk** can be easily derived. *Correlation study* - A correlation study examines the **relationship between variables** in a population, often using aggregated data, but does not follow individuals over time to assess incidence. - It can identify associations between exposures and outcomes but cannot calculate relative risk directly because it does not provide individual risk data. *Case-control study* - A case-control study compares individuals with a disease (cases) to individuals without the disease (controls) and looks back in time to determine past exposures. - While it can estimate the **odds ratio**, which approximates relative risk when the disease is rare, it cannot directly calculate relative risk because it does not provide the incidence of the disease in exposed versus unexposed populations. *Randomised control trial* - A randomized controlled trial (RCT) is an experimental study where participants are randomly assigned to an intervention or control group to assess the efficacy of an intervention. - While RCTs can calculate relative risk, they are primarily designed to establish **causality** and intervention effectiveness, not to investigate risk factors in naturally occurring populations in the same way a cohort study does for epidemiological insight.

Q: Which of the following types of study designs will be most appropriate to find out the association between mobile phone radiation exposure and cancer?

Case-control. ***Case-control*** - **Among the given options**, case-control studies are most appropriate for investigating the association between mobile phone radiation exposure and cancer. - **Case-control studies** are efficient for investigating rare outcomes like cancer, by comparing exposure histories between individuals with the disease (cases) and those without (controls). - This design allows for studying factors potentially linked to disease despite **long latency periods**. - However, note that **cohort studies** would be even more ideal for this research question as they better establish temporal relationships and minimize recall bias, which is why major studies like the INTERPHONE study used cohort designs. But cohort studies are not among the options provided. *Cross-sectional* - **Cross-sectional studies** assess exposure and outcome simultaneously, making it difficult to establish temporal relationship or causation. - They are suitable for estimating prevalence but not for investigating etiology of diseases with long latency periods like cancer. *Case-series* - A **case series** describes characteristics of a group of patients with a particular disease, but lacks a comparison group. - It cannot establish an association between exposure and outcome, as there is no control for confounding factors. *Single-arm interventional* - A **single-arm interventional study** involves administering an intervention to a single group and observing the outcome, primarily for evaluating efficacy or safety of new treatments. - It is not designed to investigate associations between environmental exposures (like mobile phone radiation) and disease, as it lacks a control group and focuses on interventions rather than observational epidemiology.

Q: A cohort study was conducted among 200 men aged 20–30 years in Rampur village. Out of 200, 120 men were tobacco users and rest 80 didn’t take any form of tobacco. At the end of one year, 40 men among tobacco users and 10 men among non-tobacco users developed tuberculosis. The incidence of tuberculosis among tobacco users is:

33.3 per 100 men/ year. ***33.3 per 100 men/year*** - **Incidence of tuberculosis among tobacco users** is calculated as (Number of new cases among tobacco users / Total number of tobacco users) × 100. - In this study, (40 / 120) × 100 = **33.3 per 100 men/year**. - This is the correct application of the **incidence rate formula** for the exposed group. *30.0 per 100 men/year* - This figure does not correspond to any standard epidemiological calculation for this study. - It may result from mathematical error or confusion with other rates. - The correct calculation for tobacco users yields 33.3, not 30.0. *12.5 per 100 men/year* - This value represents the **incidence among non-tobacco users** (10/80 × 100 = 12.5). - This answers a different question - the incidence in the unexposed group. - The question specifically asks for incidence among **tobacco users**, not non-users. *25.0 per 100 men/year* - This represents the **overall incidence** in the entire cohort: (40 + 10) / (120 + 80) × 100 = 50/200 × 100 = 25.0. - This is the total population incidence, not specific to tobacco users. - The question asks for incidence among tobacco users specifically, which requires using tobacco users as the denominator.

Q: What is the sensitivity of EEG for detecting brain tumours as per the information given below?

90%. ***90%*** - Sensitivity is calculated as **True Positives / (True Positives + False Negatives)**. - Based on the table provided, among patients with brain tumors (disease positive), 36 cases were correctly identified by EEG and 4 cases were missed. - Sensitivity = 36/(36+4) = 36/40 = 0.9 or **90%**. - This indicates that the EEG test correctly identifies 90% of patients who actually have brain tumors. - High sensitivity is important for screening tests to minimize false negatives. *99.99%* - This extremely high percentage is incorrect and not supported by the data. - It would indicate near-perfect detection of all brain tumor cases, which contradicts the table showing 4 missed cases out of 40. - Results from miscalculation or misinterpretation of the sensitivity formula. *0.07%* - This extremely low value represents a fundamental calculation error. - Such low sensitivity would indicate the test is essentially useless for detecting brain tumors. - Does not correspond to any reasonable interpretation of the given data. *85%* - While close to the correct answer, this is mathematically incorrect. - Likely results from calculation error or rounding mistakes. - The correct calculation (36/40) yields exactly 90%, not 85%.

Q: What is the attributable risk percent (etiologic fraction) of tobacco for developing tuberculosis as per the information given below? Tobacco users Tuberculosis Total Present Absent Yes 40 80 120 No 10 70 80 Total 50 150 200

62.5%. ***62.5%*** - The **risk of TB in tobacco users** is 40/120 = 0.333 (33.3%). The **risk of TB in non-tobacco users** is 10/80 = 0.125 (12.5%). - The **attributable risk (AR)** is calculated as: Risk in exposed – Risk in unexposed = 0.333 - 0.125 = 0.208 - The **attributable risk percent (AR%)** or **etiologic fraction** is: [(Risk in exposed – Risk in unexposed) / Risk in exposed] × 100 - AR% = (0.208 / 0.333) × 100 = **62.5%** - This represents the **proportion of disease in the exposed group that can be attributed to the exposure** (tobacco use). *70.6%* - This value does not result from the correct attributable risk percent formula using the provided data. - This might arise from incorrectly calculating the population attributable risk or from computational errors. *50.5%* - This percentage does not result from the appropriate calculation of attributable risk percent. - This may result from calculation errors or misapplication of the formula components. *80.6%* - This value is inconsistent with the correct calculation based on the given data. - This could result from using incorrect ratios or misunderstanding which values belong in the formula.

Question 1

The appropriate statistical test to find out obesity as a significant risk factor for breast cancer is:

Accepted Answer

Chi-square test

Answer

Wilcoxon’s signed rank test

Answer

Student’s paired ‘t’ test

Answer

Student’s unpaired ‘t’ test

Question 2

Which of the following is/are the measure(s) of dispersion?

1. Mode

2. Median

3. Standard Deviation
Select the correct answer using the code given below:

Accepted Answer

3 only

Answer

1, 2 and 3

Answer

2 and 3 only

Answer

1 and 2 only

Question 3

Analytical studies include the following methods of studies except:

Accepted Answer

Cross sectional studies

Answer

Randomised controlled trials

Answer

Cohort studies

Answer

Case control studies

Question 4

Which one of the following is not a measure of dispersion?

Accepted Answer

Mean

Answer

Mean deviation

Answer

Standard deviation

Answer

Range

Question 5

The agreement (yes/no) between two observers is statistically measured by:

Accepted Answer

Kappa coefficient

Answer

Correlation coefficient

Answer

Sensitivity

Answer

Specificity

Question 6

By which one of the following studies can relative risk be best calculated?

Accepted Answer

Cohort study

Answer

Correlation study

Answer

Case-control study

Answer

Randomised control trial

Question 7

Which of the following types of study designs will be most appropriate to find out the association between mobile phone radiation exposure and cancer?

Accepted Answer

Case-control

Answer

Cross-sectional

Answer

Case-series

Answer

Single-arm interventional

Question 8

A cohort study was conducted among 200 men aged 20–30 years in Rampur village. Out of 200, 120 men were tobacco users and rest 80 didn’t take any form of tobacco. At the end of one year, 40 men among tobacco users and 10 men among non-tobacco users developed tuberculosis. The incidence of tuberculosis among tobacco users is:

Accepted Answer

33.3 per 100 men/ year

Answer

30.0 per 100 men/ year

Answer

12.5 per 100 men/ year

Answer

25.0 per 100 men / year

Question 9

What is the sensitivity of EEG for detecting brain tumours as per the information given below?

Accepted Answer

90%

Answer

99.99%

Answer

0.07%

Answer

85%

Question 10

What is the attributable risk percent (etiologic fraction) of tobacco for developing tuberculosis as per the information given below? Tobacco users Tuberculosis Total Present Absent Yes 40 80 120 No 10 70 80 Total 50 150 200

Accepted Answer

62.5%

Answer

70.6%

Answer

50.5%

Answer

80.6%

Biostatistics — MCQs

Biostatistics — MCQs

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