Biostatistics Practice Questions

Q: For a screening test, 90% specificity means that 90% of non-diseased persons will give a

True negative result. ***True negative result*** - **Specificity** is defined as the proportion of **true negatives** among individuals **without the disease**. - A 90% specificity means that 90% of healthy individuals will correctly test negative for the disease. *False negative result* - A **false negative** occurs when a diseased person tests negative, which is related to the concept of **sensitivity**, not specificity. - This would imply missing actual cases of the disease. *True positive result* - A **true positive** occurs when a diseased person tests positive, which is also related to **sensitivity**. - This indicates accurate detection of the disease in affected individuals. *False positive result* - A **false positive** occurs when a non-diseased person inappropriately tests positive. - If 90% of non-diseased persons give a negative result (true negative), then 10% would give a **false positive result**.

Q: What is the method of sampling in which the units are picked up at regular intervals from the universe ?

Systematic random sampling. ***Systematic random sampling*** - This method involves selecting samples at a **fixed and regular interval** from a larger population after a random starting point is chosen. - It ensures representation across the entire population list by picking every nth unit, making it **efficient for large datasets**. *Stratified random sampling* - This method involves dividing the population into **homogeneous subgroups** (strata) and then drawing a random sample from each stratum. - It is used when there is a need to ensure **representation of specific subgroups**, which is not the primary characteristic described. *Snow-ball sampling* - This is a **non-probability sampling technique** where initial subjects recruit future subjects from among their acquaintances, typically used for hard-to-reach populations. - It relies on existing social networks and is not characterized by picking units at regular intervals. *Simple random sampling* - In this method, every member of the population has an **equal chance of being selected**, and selections are made fully at random. - While random, it does not involve the specific process of picking units at **regular, predetermined intervals**.

Q: A randomized trial comparing the efficacy of two drugs showed a difference between the two (p value < 0.05). However, in reality the drugs do not differ. This is an example of

Type I error. ***Type I error*** - A **Type I error** occurs when the **null hypothesis is incorrectly rejected**, leading to the conclusion that a significant difference exists when, in reality, there is no true difference. - In this scenario, the trial concluded a difference (p < 0.05), but the drugs are truly equivalent, which is precisely the definition of a **Type I error**. *Both type I and II error* - It is impossible to commit both a **Type I** and a **Type II error** simultaneously for the same statistical test. - A **Type I error** involves rejecting a true null hypothesis, while a **Type II error** involves failing to reject a false null hypothesis. *Random error* - **Random error** refers to unpredictable fluctuations in measurements or results, which can be minimized but not eliminated. - While random error can contribute to variability in data, it is not the direct statistical error of concluding a non-existent difference when analyzing the results, which is a **Type I error**. *Type II error* - A **Type II error** occurs when the **null hypothesis is incorrectly accepted** (or not rejected), meaning a real difference exists but the study fails to detect it. - This scenario describes the opposite: a difference was detected and concluded, but it was false.

Q: In a village, every fifth house was selected for a study. This is an example of

Systematic random sampling. ***Systematic random sampling*** - This method involves selecting subjects from a **ordered sampling frame** at regular intervals, such as every k-th item. - In this scenario, selecting every fifth house represents a fixed interval (k=5), which is characteristic of systematic random sampling. *Simple random sampling* - This method ensures that every member of the population has an **equal chance of being selected**, often through random number generation. - It does not involve a predetermined, fixed interval of selection from an ordered list. *Convenience sampling* - This technique involves selecting subjects who are **easily accessible or readily available**, without any systematic or random process. - It is prone to bias as it does not represent the entire population. *Stratified random sampling* - This method involves dividing the population into **homogeneous subgroups (strata)** and then conducting simple random sampling within each stratum. - The scenario does not describe dividing the village households into distinct subgroups before selection.

Q: The ability of a test to identify correctly those who do not have the disease is called its

Specificity. ***Specificity*** - **Specificity** is the proportion of **true negatives** correctly identified by the test. - It measures the ability of a test to correctly identify individuals who **do not have the disease**. *Sensitivity* - **Sensitivity** is the proportion of **true positives** correctly identified by the test. - It measures the ability of a test to correctly identify individuals who **do have the disease**. *Positive predictive value* - **Positive predictive value (PPV)** is the probability that a patient with a **positive test result** actually has the disease. - It depends on the **prevalence** of the disease in the population being tested. *Negative predictive value* - **Negative predictive value (NPV)** is the probability that a patient with a **negative test result** actually does not have the disease. - It also depends on the **prevalence** of the disease in the population.

Q: In a normal curve, how much per cent of the values will be included in the area between two standard deviations on either side of the mean (X ± 2σ) ?

95.4. ***Correct: 95.4*** - According to the **empirical rule** (also known as the 68-95-99.7 rule), approximately 95% of data falls within two standard deviations of the mean in a normal distribution. - More precisely, the area between **X ± 2σ** encompasses **95.4%** of the values. - This is a fundamental concept in biostatistics used for calculating confidence intervals and reference ranges. *Incorrect: 68.3* - This percentage represents the proportion of data within **one standard deviation** (X ± 1σ) of the mean in a normal distribution. - It is not the correct value for the range of two standard deviations. *Incorrect: 90.4* - This value does not correspond to any standard interval of standard deviations around the mean in a normal distribution. - It is not part of the empirical rule for common standard deviation ranges. *Incorrect: 99.7* - This percentage represents the proportion of data within **three standard deviations** (X ± 3σ) of the mean in a normal distribution. - It is a larger interval than what is asked in the question (two standard deviations).

Q: A new drug is to be evaluated for its therapeutic effect. The best study design will be.

Randomized controlled trial. ***Randomized controlled trial*** - This design is the **gold standard** for evaluating the effectiveness of a new therapeutic intervention. - **Randomization** minimizes confounding, and a control group allows for direct comparison of outcomes, isolating the **drug's effect**. *Natural experiment* - This design involves observing the effects of an intervention that occurs naturally, without researcher manipulation. - It lacks the **control** and **randomization** necessary to definitively attribute observed effects solely to the therapeutic agent. *Cross sectional survey* - This design assesses the prevalence of a condition or exposure at a single point in time. - It cannot establish **causality** or evaluate the therapeutic effect of an intervention over time. *Case control design* - This retrospective design compares individuals with a disease (cases) to those without (controls) to identify past exposures. - It is used to investigate **risk factors** for diseases, not to evaluate the therapeutic efficacy of a new drug.

Q: "Sampling error" occurs due to the variation in results

between one sample and another. ***between one sample and another*** - **Sampling error** arises because a sample is not a perfect representation of the entire population from which it is drawn. - This error quantifies the natural **variability** that occurs when different subgroups (samples) are selected from the same population. *due to the use of many instruments in the study* - This scenario describes **inter-instrument variability** or **measurement error**, which is related to the precision and calibration of different tools. - While it can introduce error, it is distinct from sampling error, which arises from the representativeness of the chosen study subjects. *due to the multiple readings taken on the same instrument* - Multiple readings on the same instrument assess **intra-instrument variability** or **repeatability**, indicating how consistent a single instrument is over time. - This relates to the precision of the measurement device, not the representativeness of the sample itself. *between the observations of two individuals* - Differences in observations between two individuals indicate **inter-rater variability** or **observer bias**. - This type of error is related to subjective interpretation or measurement technique by different observers, rather than the intrinsic variability between selected samples.

Q: The "Relative Risk" of 0.25 indicates

75% reduction in the incidence rate in the exposed individuals compared with the unexposed. ***75% reduction in the incidence rate in the exposed individuals compared with the unexposed*** - A **Relative Risk (RR)** of 0.25 means the risk in the exposed group is 25% of the risk in the unexposed group. - This indicates a **reduction** in risk calculated as (1 - RR) * 100%, so (1 - 0.25) * 100% = 75% reduction. *2.5 times higher risk in the exposed individuals compared with the unexposed* - This would be indicated by an RR of 2.5, meaning the risk is **2.5 times greater** in the exposed group. - An RR of 0.25 signifies a risk that is **less than** that of the unexposed group, not higher. *25% increase in the incidence rate in the exposed individuals compared with the unexposed* - A 25% increase would mean the RR is 1.25 (1 + 0.25), indicating a **higher risk** in the exposed group. - An RR of 0.25 represents a **decrease** in risk, not an increase. *75% risk increase in the exposed individuals compared with the unexposed* - A 75% risk increase would correspond to an RR of 1.75 (1 + 0.75), suggesting a **greater risk**. - With an RR of 0.25, the risk in the exposed group is **lower**, representing a reduction rather than an increase.

Q: Which is the fertility indicator that gives the approximate magnitude of completed family size?

Total Fertility Rate. ***Total Fertility Rate*** - The **Total Fertility Rate (TFR)** estimates the average number of children a woman would have over her lifetime if she were to experience current age-specific fertility rates. - It provides a measure of the **completed family size** in a hypothetical cohort of women. *Age-specific Fertility Rate* - The **Age-specific Fertility Rate (ASFR)** measures the number of births to women in a particular age group per 1,000 women in that age group. - It does not directly provide the completed family size but is a component used to calculate the TFR. *General Fertility Rate* - The **General Fertility Rate (GFR)** calculates the number of live births per 1,000 women of childbearing age (typically 15-49 years) in a given year. - While it reflects overall fertility, it does not provide an estimate of the completed family size per woman. *Gross Reproduction Rate* - The **Gross Reproduction Rate (GRR)** is similar to the TFR but only considers female births. - It estimates the average number of daughters a woman would have over her lifetime based on current age-specific fertility rates, without accounting for mortality.

Question 1

For a screening test, 90% specificity means that 90% of non-diseased persons will give a

Accepted Answer

True negative result

Answer

False negative result

Answer

True positive result

Answer

False positive result

Question 2

What is the method of sampling in which the units are picked up at regular intervals from the universe ?

Accepted Answer

Systematic random sampling

Answer

Stratified random sampling

Answer

Snow-ball sampling

Answer

Simple random sampling

Question 3

A randomized trial comparing the efficacy of two drugs showed a difference between the two (p value < 0.05). However, in reality the drugs do not differ. This is an example of

Accepted Answer

Type I error

Answer

Both type I and II error

Answer

Random error

Answer

Type II error

Question 4

In a village, every fifth house was selected for a study. This is an example of

Accepted Answer

Systematic random sampling

Answer

Simple random sampling

Answer

Convenience sampling

Answer

Stratified random sampling

Question 5

The ability of a test to identify correctly those who do not have the disease is called its

Accepted Answer

Specificity

Answer

Sensitivity

Answer

Positive predictive value

Answer

Negative predictive value

Question 6

In a normal curve, how much per cent of the values will be included in the area between two standard deviations on either side of the mean (X ± 2σ) ?

Accepted Answer

95.4

Answer

68.3

Answer

90.4

Answer

99.7

Question 7

A new drug is to be evaluated for its therapeutic effect. The best study design will be.

Accepted Answer

Randomized controlled trial

Answer

Natural experiment

Answer

Cross sectional survey

Answer

Case control design

Question 8

"Sampling error" occurs due to the variation in results

Accepted Answer

between one sample and another

Answer

due to the use of many instruments in the study

Answer

due to the multiple readings taken on the same instrument

Answer

between the observations of two individuals

Question 9

The "Relative Risk" of 0.25 indicates

Accepted Answer

75% reduction in the incidence rate in the exposed individuals compared with the unexposed

Answer

2.5 times higher risk in the exposed individuals compared with the unexposed

Answer

25% increase in the incidence rate in the exposed individuals compared with the unexposed

Answer

75% risk increase in the exposed individuals compared with the unexposed

Question 10

Which is the fertility indicator that gives the approximate magnitude of completed family size?

Accepted Answer

Total Fertility Rate

Answer

Age-specific Fertility Rate

Answer

General Fertility Rate

Answer

Gross Reproduction Rate

Biostatistics — MCQs

Biostatistics — MCQs

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