Biostatistics

Experimental designs, though powerful in establishing cause-effect relationships, have certain limitations:

• Ethical issues may arise concerning participant rights and well-being.
• They often involve small sample sizes due to resource constraints.
• The sample may not always represent the broader population, limiting generalizability.

However, the ability to replicate findings is a strength of experimental designs, not a limitation, as the controlled conditions allow for consistency in repeated studies.

The hierarchy of research designs with respect to hypothesis testing and cause-effect relationships starts with the least structured and progresses to the most rigorous:

• Exploratory qualitative designs (B): Least structured, used to explore phenomena without a strong focus on hypothesis testing.
• Cross-sectional quantitative designs (D): Provide a snapshot of data at a single point in time, often used for correlations.
• Longitudinal designs (C): Track changes over time, helping to establish temporal sequences.
• Experimental designs (A): Most structured and effective for testing hypotheses and establishing cause-effect relationships.

• 14% or more have normal morphology: This indicates a healthy sperm morphology, critical for fertility.
• 75% or more are alive: High viability ensures functional sperm capable of fertilization.
• 50% or more with moderate to rapid linear progression: Forward motility is essential for reaching and fertilizing the egg.
• Option (C): is not included as the standard threshold for sperm concentration is higher than sperm/mL.

The correct matches are:

• A. Specific death rate due to tuberculosis: Denominator is Mid-year population as it measures deaths due to tuberculosis in the general population.
• B. Specific death rate for males: Denominator is Mid-year population of males, focusing on male-specific death rates.
• C. Case fatality rate for COVID-19: Denominator is Total number of COVID-19 cases, as it measures deaths among confirmed cases.
• D. Specific death rate in age group 15-19 years: Denominator is Mid-year population of persons aged 15-19, as it assesses deaths in this specific age group.

Thus, the correct sequence is: (A) - (II), (B) - (III), (C) - (I), (D) - (IV).

Measures of variation or dispersion describe the spread or variability in a dataset.
The following are considered measures of dispersion:

• Standard deviation: Quantifies the amount of variation or dispersion in a dataset.
• Range: The difference between the maximum and minimum values in a dataset.
• Mean deviation: The average of the absolute deviations of data points from the mean.

Mean is a measure of central tendency, not dispersion. Therefore, the correct answer includes only options (B), (C), and (D).

Probability sampling methods are those in which each unit in the population has a known and non-zero chance of being selected. These include:

• Simple random sampling: Every individual has an equal probability of being chosen.
• Systematic random sampling: Selection occurs at regular intervals from a list.
• Stratified random sampling: The population is divided into subgroups (strata), and random samples are taken from each stratum.

Purposive sampling is a non-probability sampling method where participants are selected based on specific characteristics or judgment, not randomization.

Thus, the correct answer is (A), (B), and (C) only.

To determine the median diastolic blood pressure for each patient, arrange the values in ascending order:

1. (A): 71, 71, 79, 81, 83
   Median = 79
2. (B): 75, 83, 89, 90, 90
   Median = 89
3. (C): 70, 72, 75, 87, 87
   Median = 75
4. (D): 75, 81, 84, 95, 95
   Median = 84

Arranging in increasing order of median: (C) (75), (A) (79), (D) (84), (B) (89). Thus, the correct sequence is (C), (A), (D), (B).

The steps involved in conducting a Randomised Controlled Trial (RCT) are:

1. Drawing up a protocol: This is the first step where the objectives, methodology, and plan for the trial are outlined.
2. Randomisation: Participants are randomly assigned to different intervention groups to eliminate selection bias.
3. Intervention or manipulation: The intervention being studied is applied to the relevant group(s).
4. Assessment of outcome: The results of the intervention are measured to determine its effectiveness.

Thus, the correct sequence is (B), (A), (C), (D).

The mode of a dataset is the value that appears most frequently. Analyzing the given dataset:
35, 44, 33, 35, 37, 44, 37, 35
The frequency of each value is:

• 35: 3 times
• 44: 2 times
• 33: 1 time
• 37: 2 times

Since 35 appears the most (3 times), the mode is 35.

The range of a dataset is calculated as the difference between the maximum and minimum values in the dataset.

Maximum value: 44, Minimum value: 35.45

Range: 35.45 to 44. The closest option that includes this range is 35 to 50.

A nominal variable is a categorical variable that has no intrinsic ordering or rank.”Mother-tongue” represents a category (e.g., English, Hindi, French) without any quantitative value or natural order. In contrast, variables like blood sugar level, temperature, and cost of a cup of tea are continuous or ordinal in nature.

A line diagram is the best choice to show the trend of events over time because it allows for the visualization of continuous changes. It connects data points with lines, making it easier to identify patterns or trends in the data over a period.

The paired t-test is a statistical test used to compare the means of a continuous variable measured on the same subjects before and after an intervention. This test accounts for the dependency between the two sets of data since the measurements are taken from the same individuals.

The Chi-square test is a non-parametric statistical test used for bivariate analysis when both variables are categorical. It examines the association or independence between two categorical variables by comparing the observed and expected frequencies in a contingency table.

• Independent t-test: Compares means of two independent groups.
• Paired t-test: Compares means of the same group at two different times.
• ANOVA: Compares means of more than two groups.
• Chi-square test: Used for categorical data, not means.

• Paired t-test is for related samples.
• ANOVA is for more than two groups.
• Chi-square is for categorical variables.