Biostatistics Practice Questions

Q: For calculation of sample size for a prevalence study, all of the following are necessary except:

Power of the study. ***Power of the study*** - The **power of a study** is primarily relevant when calculating sample sizes for **hypothesis testing** (e.g., comparing two groups) to detect a statistically significant difference if one exists. - In a prevalence study, the goal is to estimate a proportion or prevalence with a certain level of precision, rather than to test a hypothesis. *Prevalence of disease in population* - An **estimated prevalence** is crucial for sample size calculation in prevalence studies, as it directly influences the variability of the proportion being estimated. - A higher or lower estimated prevalence affects the required sample size to achieve a desired level of precision. *Significance level* - The **significance level (alpha)** defines the probability of rejecting the null hypothesis when it is true (Type I error). - While essential for hypothesis testing, it is still used in prevalence studies to define the **confidence level** for the estimated prevalence (e.g., 95% confidence interval corresponds to an alpha of 0.05). *Desired precision* - **Desired precision**, often expressed as the **margin of error**, is a fundamental component of sample size calculation for prevalence studies. - It specifies how close the sample estimate should be to the true population prevalence.

Q: What does specificity in a diagnostic test measure?

True negative. ***True negative*** - Specificity measures the **proportion of true negatives** correctly identified by the test. - It indicates the test's ability to correctly identify individuals **without the disease** who test negative. - **Formula: Specificity = TN / (TN + FP)** where TN = True Negatives, FP = False Positives. *True positive* - **True positives** are measured by **sensitivity**, not specificity. - Sensitivity measures the proportion of people with the disease who test positive. *False positive* - **False positives** reduce specificity but are not what specificity measures. - High specificity means fewer false positives (more specific for the disease). *False negative* - **False negatives** are related to **sensitivity**, not specificity. - A test with low sensitivity will have a higher rate of false negatives.

Q: Which of the following is not a method of random sampling?

Quota sampling. ***Quota sampling*** - **Quota sampling** is a non-probability sampling method where researchers select a sample based on pre-defined characteristics to match the population's proportions. - It does not involve random selection at any stage, making it a non-random sampling technique. *Cluster sampling* - **Cluster sampling** is a probability (random) sampling technique where the population is divided into clusters, and then a random sample of these clusters is selected. - All units within the selected clusters are then included in the sample, or a random sample is taken from within the selected clusters. *Stratified sampling* - **Stratified sampling** is a probability (random) sampling method that involves dividing the population into homogeneous subgroups (strata) and then taking a random sample from each stratum. - This method ensures representation from all important subgroups within the population. *Simple random* - **Simple random sampling** is a basic probability (random) sampling technique where every member of the population has an equal chance of being selected for the sample. - This method is considered the most fundamental type of random sampling.

Q: Which of the following statements about the normal distribution curve is true?

Mean = Median. ***Mean = Median*** - In a **normal distribution curve**, the data is perfectly symmetrical around its center. - This symmetry ensures that the **mean, median, and mode** all coincide at the peak of the curve. - This is a defining characteristic of the **Gaussian (normal) distribution**. *Mean = 2 Median* - This statement is incorrect; in a **normal distribution**, the mean and median are equal, not a multiple of each other. - Such a relationship (Mean = 2 Median) would imply a **positively skewed distribution**, which is not characteristic of a normal distribution. *Median = Variance* - The **median** is a measure of **central tendency**, representing the middle value of the data set. - **Variance** is a measure of **data dispersion** (how spread out the data is), measured in squared units. - These two measures are fundamentally different concepts and generally not equal. *Standard Deviation = 2 Variance* - **Standard deviation** is the **square root of the variance** (SD = √Variance), not twice the variance. - This relationship is mathematically incorrect and does not hold true for any distribution.

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: 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: 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: 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.

Question 1

This study found a correlation coefficient of +0.7 between self-reported work satisfaction and life expectancy in a random sample of 5,000 corporate workers, with a p-value of 0.01. This means that:

Accepted Answer

Strong statistically significant (+) association between work satisfaction and life expectancy.

Answer

Correlation does not imply that 70% of people who enjoy work shall live longer.

Answer

Correlation coefficient of +0.7 indicates a moderate positive relationship, not a percentage.

Answer

Work satisfaction is moderately associated with life expectancy.

Question 2

For calculation of sample size for a prevalence study, all of the following are necessary except:

Accepted Answer

Power of the study

Answer

Significance level

Answer

Desired precision

Answer

Prevalence of disease in population

Question 3

What does specificity in a diagnostic test measure?

Accepted Answer

True negative

Answer

True positive

Answer

False positive

Answer

False negative

Question 4

Which of the following is not a method of random sampling?

Accepted Answer

Quota sampling

Answer

Cluster sampling

Answer

Stratified sampling

Answer

Simple random

Question 5

After applying a statistical test, an investigator gets a p-value of 0.01. What does this indicate about the null hypothesis?

Accepted Answer

There is a 1% probability of observing the data, or something more extreme, if the null hypothesis is true.

Answer

There is a 1% probability of incorrectly rejecting the null hypothesis when it is true.

Answer

The test has a 99% chance of detecting a true effect if it exists.

Answer

The null hypothesis is likely to be rejected.

Question 6

Which of the following statements about the normal distribution curve is true?

Accepted Answer

Mean = Median

Answer

Mean = 2 Median

Answer

Median = Variance

Answer

Standard Deviation = 2 Variance

Question 7

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 8

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 9

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 10

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.

Biostatistics — MCQs

Biostatistics — MCQs

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