Okay, let's tackle this question. The user wants me to figure out the correct answer and write a detailed explanation. The question is about a sampling method where units are picked at regular intervals.

First, I need to recall different sampling methods. There's simple random sampling, stratified, cluster, systematic, and others. The key term here is "regular intervals." That makes me think of systematic sampling. In systematic sampling, you select every kth element from a list after a random start. For example, if you have a population of 1000 and need a sample of 100, you'd pick every 10th person.

Now, let's look at the options. The correct answer is D. Systematic Sampling. The other options would be things like stratified, cluster, or simple random.

Why is systematic correct? Because it's the method where you select units at regular intervals. The interval is calculated based on the population size divided by the sample size. The process starts with a random number between 1 and the interval size, then every kth element is selected. This method is efficient and ensures spread across the population.

For the incorrect options: Stratified divides the population into subgroups (strata) and samples from each. Cluster sampling divides into clusters, randomly selects clusters, and samples all within them. Simple random is purely random without any systematic approach. None of these involve regular intervals.

The clinical pearl here is that systematic sampling is easy to implement and avoids clustering, but can introduce bias if there's a periodic pattern in the population. So, it's important to check for periodicity in the data when using this method.

**Core Concept**
The question examines **systematic sampling**, a probability sampling technique where elements are selected from a population at regular intervals. This method is distinct from random or stratified sampling and relies on a fixed, periodic interval (k) to select samples.

**Why the Correct Answer is Right**
**Systematic sampling** involves selecting units from a population at uniform intervals (e.g., every 5th or 10th individual). The interval (k) is calculated as the population size divided by the desired sample size. For example, if the population is 1000 and the sample size is 100, k = 10, and every 10th individual is selected starting from a random starting point. This method ensures even coverage of the population and is efficient for large datasets.

**Why Each Wrong Option is Incorrect**
**Option A:** *Simple random sampling* involves random selection without a fixed interval, making it less structured.
**Option B:** *Stratified sampling* divides the population into subgroups (strata) and samples proportionally from each, not via intervals.
**Option C:** *Cluster sampling* groups the population into clusters, randomly selects clusters, and samples all units within them—unrelated to fixed intervals.

**Clinical Pearl / High-Yield Fact**
Systematic sampling is favored for its simplicity and low cost but risks periodic bias if the population has hidden patterns (e.g., alternating male/female). Always verify for periodicity before applying this method. A mnemonic: **"Systematic = Step-by-step selection."**

**Correct Answer: D. Systematic Sampling**

✓ Correct Answer: B. Systematic random sampling