**Core Concept:** Equal interval bias is a type of selection bias that occurs when the sampling frame is not randomly divided into equal segments, leading to an unequal representation of the population in each segment.

**Why the Correct Answer is Right:** The correct answer, Option D, refers to the concept of "Random Sampling" which is the only strategy that can effectively reduce equal interval bias. In random sampling, the sampling frame (list of all individuals/units to be included in the study) is divided into equal segments using a random number generator or a random sequence (e.g., using a random number table or a computer program). This ensures that each individual or unit has an equal chance of being selected into the study, preventing any unequal representation of the population in the sampling frame.

**Why Each Wrong Option is Incorrect:**

A. Option A, "Selection by Stratified Sampling," is not effective in reducing equal interval bias because it still relies on manually dividing the sampling frame into equal segments, which can introduce bias.

B. Option B, "Selection by Quota Sampling," is incorrect as it involves selecting a predetermined number of participants from each segment based on pre-defined criteria, not random selection. This increases the risk of equal interval bias and other non-random biases.

C. Option C, "Selection by Convenience Sampling," is also not suitable for reducing equal interval bias because it involves selecting participants based on their availability or accessibility, which is not random and may result in unequal representation of the population.

D. Random Sampling ensures equal interval bias is reduced because it guarantees that each segment in the sampling frame has an equal chance of being selected, ensuring an unbiased sample.

**Clinical Pearl:** To minimize bias in sampling and obtain a representative sample for research or clinical studies, using random sampling techniques is crucial. Utilizing random sampling helps ensure that the sample is unbiased and allows for accurate generalization of findings to the larger population.