**Logistic Curve**

The correct answer is option 'C', the logistic curve. The growth of population can be conveniently represented by a logistic curve, which is a type of S-shaped curve that is commonly used to model exponential growth in the early stages and then levels off as it approaches a maximum limit. The logistic curve is often used in population studies because it takes into account the limiting factors that affect population growth, such as available resources and carrying capacity.

**Explanation:**

1. **Population Growth:** The growth of a population refers to the increase in the number of individuals in a population over time. It can be influenced by various factors such as birth rate, death rate, immigration, and emigration.

2. **Curve Representation:** In order to represent the population growth mathematically, a curve is used. This curve describes the relationship between the population size and time.

3. **Types of Curves:** There are different types of curves that can be used to represent population growth, depending on the specific characteristics of the growth pattern. Some common types of curves used in population studies include exponential, logistic, semilog, and straight line curves.

4. **Exponential Curve:** An exponential curve represents a constant rate of growth, where the population size increases at an accelerating rate. In this type of curve, the population size doubles within a fixed time period.

5. **Straight Line Curve:** A straight line curve represents a linear growth pattern, where the population size increases at a constant rate over time. This type of curve is rarely used to represent population growth because it does not account for limiting factors.

6. **Semilog Curve:** A semilog curve is a combination of exponential and linear growth patterns. In this type of curve, one axis is represented on a logarithmic scale, while the other axis is represented on a linear scale. This allows for a more accurate representation of exponential growth.

7. **Logistic Curve:** The logistic curve is the most suitable curve for representing population growth because it takes into account the limiting factors that affect population growth. Initially, the curve shows exponential growth, but as the population approaches its carrying capacity (the maximum number of individuals that the environment can support), the growth rate slows down and eventually levels off.

8. **Conclusion:** The growth of population can be conveniently represented by a logistic curve because it accurately models the exponential growth in the early stages and the leveling off as the population approaches its carrying capacity. This curve is widely used in population studies and provides a mathematical solution to represent population growth accurately.