Biostatistics Practice Questions

Q: What is the definition of literacy according to census standards?

Ability to read and write. ***Ability to read and write*** - According to most census standards, **literacy** is fundamentally defined as the ability of an individual to **read and write a simple message** in any language. - This definition focuses on the basic functional capacity to engage with written communication, rather than advanced proficiency. *Participation in a literacy program* - While participating in a literacy program indicates an effort towards improving literacy, it does not, by itself, define the current **literacy status** according to census standards. - An individual might attend such a program without yet acquiring the functional ability to **read and write**. *Ability to read and write fluently* - **Fluency** implies a high level of proficiency and speed in reading and writing, which goes beyond the basic definition of literacy used in census data collection. - Census standards typically only require the **basic capacity** to read and write. *Ability to write a simple sentence* - This option only covers the **writing aspect** of literacy and omits the crucial component of being able to **read**. - Census definitions require both reading and writing capabilities to be considered literate.

Q: Specificity of a diagnostic test is defined as:

0.95. ***0.95*** - **Specificity** is the proportion of individuals without disease who test negative, calculated as **TN/(TN+FP)**. - A specificity of 0.95 (95%) indicates an excellent test that correctly identifies 95% of healthy individuals as negative. *0.05* - This value represents the **false positive rate** (1 - specificity), not specificity itself. - A specificity of 0.05 would mean only 5% of healthy individuals test negative, indicating a very poor test. *0.4* - This value is too low for specificity and could represent other test parameters like **positive predictive value**. - A specificity of 0.4 would incorrectly classify 60% of healthy individuals as positive, making the test clinically unreliable. *0.8* - This value typically represents **sensitivity**, which is the proportion of diseased individuals who test positive. - **Sensitivity** is calculated as **TP/(TP+FN)**, which is different from specificity that focuses on healthy individuals.

Q: In the context of medical statistics, which graphical representation is used to show the proportion of different categories of a variable in a dataset?

Pie. ***Option A: Pie*** - A **pie chart** is ideal for displaying **proportions** of different categories within a whole, where each slice represents a percentage of the total. - It clearly shows how each category contributes to the **overall dataset**, making it easy to visualize relative frequencies and the **part-to-whole relationship**. *Option B: Bar* - A **bar graph** is typically used to compare the **magnitudes** or frequencies of different categorical variables, rather than their proportion of a whole. - While it can show counts for categories, it doesn't directly represent the **part-to-whole relationship** as effectively as a pie chart. *Option C: Histogram* - A **histogram** is used to represent the **distribution of continuous numerical data**, grouping values into bins and displaying their frequencies. - It is not suitable for showing proportions of different **categorical variables**. *Option D: Pictogram* - A **pictogram** uses **pictures or symbols** to represent data, often in a simplified and engaging way. - While it can represent frequencies or counts, it is less precise for showing exact **proportions** of categories compared to a pie chart.

Q: Which of the following is obtained by joining the midpoints of histogram blocks in statistics?

Frequency polygon. ***Frequency polygon*** - A **frequency polygon** is constructed by plotting a point at the midpoint of the top of each histogram bar and then connecting these points with straight lines. - It is used to display the **frequency distribution** of continuous data, similar to a histogram, but can also compare multiple distributions on one graph. *Pictogram* - A **pictogram** uses images or symbols to represent data, where each symbol represents a certain quantity. - It simplifies data for broader audiences but is not derived directly from histogram blocks. *Bar chart* - A **bar chart** uses rectangular bars of varying heights or lengths to represent data for different categories. - Unlike a histogram, bar charts typically represent **categorical data** and have gaps between bars. *Pie chart* - A **pie chart** is a circular statistical graphic divided into slices to illustrate numerical proportion. - Each slice represents a category's proportion of the whole and is not related to histogram blocks or their midpoints.

Q: Which of the following statements about screening tests is correct?

Sensitivity is 1 - False negative rate. ***Sensitivity is 1 - False negative rate*** - **Sensitivity** refers to the proportion of **true positive results** among all individuals with the disease. - The **false negative rate** is the proportion of individuals with the disease who test negative, so **1 - false negative rate** correctly defines sensitivity. *Sensitivity is 1 - False positive rate* - The false positive rate (1 - specificity) is related to the proportion of individuals without the disease who test positive. - This statement incorrectly defines sensitivity, confusing it with concepts related to specificity. *Post-test probability is only influenced by pre-test probability* - **Post-test probability** is influenced by both the **pre-test probability** and the **likelihood ratio** of the diagnostic test. - The **likelihood ratio** incorporates the test's sensitivity and specificity, making it a critical factor in modifying the probability of disease after testing. *None of the options is correct.* - The first statement, "Sensitivity is 1 - False negative rate," is a correct definition of sensitivity.

Q: Which of the following is not considered a type of subject bias?

Selection bias. ***Selection bias*** - **Selection bias** occurs when participants are chosen or remain in a study in a way that introduces a systematic error, leading to a sample that does not accurately represent the target population. - It is a **study design and sampling issue** that occurs at the **recruitment** or **retention stage**, not a bias arising from the subjects' own behavior or reporting. - Unlike subject biases, selection bias is introduced by the **investigators or study methodology**, not by the participants themselves. *Recall bias* - **Recall bias** is a type of **subject bias** where participants differentially remember and report past exposures based on their outcome status. - Subjects with disease may recall exposures more accurately than healthy controls, introducing **systematic error from the subject's memory**. *Hawthorne bias* - **Hawthorne bias** (observer effect) is a **subject bias** where participants modify their behavior because they know they are being studied. - The **subject's awareness** of observation directly influences their actions, responses, or adherence. *Reporting bias* - **Reporting bias** is a **subject bias** where participants selectively disclose or withhold information based on social desirability, embarrassment, or perceived consequences. - This bias arises from the **subject's decision** about what to report.

Q: Central value of a set of 180 values can be obtained by which of the following?

2nd quartile. ***2nd quartile*** - The **2nd quartile** is equivalent to the **median**, which represents the central value of a dataset. - For 180 values, the median (Q2) would be located between the 90th and 91st values when ordered, effectively dividing the data into two equal halves. *2nd tertile* - The 2nd tertile divides the data into three equal parts, signifying the value below which two-thirds of the data lie, not the central value. - For 180 values, the 2nd tertile would be around the 120th ordered value (2/3 of 180), which is far from the center. *80th percentile* - The 80th percentile indicates that 80% of the data falls below this value. - This is a measure of a specific position within the upper portion of the data, not the central tendency. *9th decile* - The 9th decile represents the value below which 90% of the data falls. - This value is very high in the dataset and does not represent the central value.

Q: What is the correct formula for calculating the positive predictive value (PPV) of a screening test?

True positives / (True positives + False positives). ***True positives / (True positives + False positives)*** - **Positive predictive value (PPV)** indicates the probability that a patient who tests positive actually has the disease. - It is calculated by dividing the number of **true positives** (correctly identified positive cases) by the total number of positive test results (**true positives + false positives**). *True positives / (True positives + False negatives)* - This formula represents the **sensitivity** of a test, which is the proportion of actual positive cases that are correctly identified. - Sensitivity measures the ability of a test to correctly identify individuals with the disease. *False positives / (False positives + True negatives)* - This formula represents **1 - specificity**, or the **false positive rate**. - **Specificity** is the proportion of actual negative cases that are correctly identified as negative. *True negatives / (True negatives + False negatives)* - This formula represents the **negative predictive value (NPV)**, which is the probability that a patient who tests negative actually does not have the disease. - NPV is calculated by dividing the number of **true negatives** (correctly identified negative cases) by the total number of negative test results (**true negatives + false negatives**).

Q: The fundamental equilibrium principle of population genetics was given by?

Hardy Weinberg. ***Hardy Weinberg*** - The **Hardy-Weinberg principle** describes the conditions under which allele and genotype frequencies in a population remain constant from generation to generation. - It established the baseline for understanding when evolutionary forces like **mutation**, **selection**, **gene flow**, and **genetic drift** are acting on a population. *Sewall Wright* - Sewall Wright is known for his work on **genetic drift**, particularly the concept of the **effective population size** and the **shifting balance theory** of evolution. - While fundamental to population genetics, his contributions did not lay the initial equilibrium principle. *J. B. S. Haldane* - J.B.S. Haldane made significant contributions to the **mathematical theory of natural selection** and was a pioneer in developing population genetics as a field. - He focused more on the dynamics of evolution under selection rather than the foundational equilibrium state. *R. A. Fisher* - R. A. Fisher was a key figure in modern statistics and population genetics, known for developing concepts like **Fisher's fundamental theorem of natural selection** and the **evolution of dominance**. - His work built upon the Hardy-Weinberg equilibrium, explaining how selection drives evolutionary change.

Q: Which scale is also known as the Cumulative Scale?

Guttman Scale. ***Guttman Scale*** - The **Guttman scale**, also known as the **cumulative scale**, is designed such that if an individual agrees with a more extreme statement, they will also agree with all less extreme statements - It measures a **single, unidimensional trait**, and responses are ordered cumulatively - This cumulative property is what gives it the name "Cumulative Scale" *Visual Analog Scale* - The **Visual Analog Scale (VAS)** is a psychometric response scale used to measure subjective characteristics or attitudes that cannot be directly measured - It typically presents a **continuous line** where patients mark their current state, most commonly used for pain assessment - Not a cumulative scale *Thurstone Scale* - A **Thurstone scale** uses a panel of judges to assign numeric values to attitude statements based on their perceived intensity or favorability - It aims to create an **interval scale** where the distance between categories is assumed to be equal - Does not have cumulative properties *Semantic Differential Scale* - The **Semantic Differential Scale** measures the connotative meaning of concepts or objects - Asks respondents to rate a concept on a series of **bipolar adjective pairs** (e.g., good-bad, strong-weak) - Used to assess perceptions and attitudes rather than cumulative agreement

Question 1

What is the definition of literacy according to census standards?

Accepted Answer

Ability to read and write

Answer

Participation in a literacy program

Answer

Ability to read and write fluently

Answer

Ability to write a simple sentence

Question 2

Specificity of a diagnostic test is defined as:

Accepted Answer

0.95

Answer

0.05

Answer

0.4

Answer

0.8

Question 3

In the context of medical statistics, which graphical representation is used to show the proportion of different categories of a variable in a dataset?

Accepted Answer

Pie

Answer

Bar

Answer

Histogram

Answer

Pictogram

Question 4

Which of the following is obtained by joining the midpoints of histogram blocks in statistics?

Accepted Answer

Frequency polygon

Answer

Pictogram

Answer

Bar chart

Answer

Pie chart

Question 5

Which of the following statements about screening tests is correct?

Accepted Answer

Sensitivity is 1 - False negative rate

Answer

Sensitivity is 1 - False positive rate

Answer

Post-test probability is only influenced by pre-test probability

Answer

None of the options is correct.

Question 6

Which of the following is not considered a type of subject bias?

Accepted Answer

Selection bias

Answer

Recall bias

Answer

Hawthorne bias

Answer

Reporting bias

Question 7

Central value of a set of 180 values can be obtained by which of the following?

Accepted Answer

2nd quartile

Answer

2nd tertile

Answer

80th percentile

Answer

9th decile

Question 8

What is the correct formula for calculating the positive predictive value (PPV) of a screening test?

Accepted Answer

True positives / (True positives + False positives)

Answer

True positives / (True positives + False negatives)

Answer

False positives / (False positives + True negatives)

Answer

True negatives / (True negatives + False negatives)

Question 9

The fundamental equilibrium principle of population genetics was given by?

Accepted Answer

Hardy Weinberg

Answer

Sewall Wright

Answer

J. B. S. Haldane

Answer

R. A. Fisher

Question 10

Which scale is also known as the Cumulative Scale?

Accepted Answer

Guttman Scale

Answer

Thurstone Scale

Answer

Visual Analog Scale

Answer

Semantic Differential Scale

Biostatistics — MCQs

Biostatistics — MCQs

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