Concentration vs Distance plots resemble _____________ .
Lognormal distribution
Binomial distribution
Lorentzian distribution
Gaussian distribution
The concentration vs distance plots typically resemble the Gaussian distribution.
To understand why, let's first delve into what a concentration vs distance plot represents. In many scientific fields, such as chemistry or biology, concentration refers to the amount of a specific substance present in a given space or volume. Distance, on the other hand, signifies the physical separation between two points.
When plotting the concentration of a substance against the distance, we often obtain a bell-shaped curve. This shape is characteristic of the Gaussian (or normal) distribution, which is widely used to represent natural phenomena.
The Gaussian distribution is recognized by its symmetric shape, with the highest concentration value at the peak of the curve. It is often observed in situations where multiple independent factors contribute to the overall concentration, following the principle of central limit theorem.
To obtain concentration vs distance plots, experimental data is usually collected at various distances from a source, and the concentration is measured at each point. By plotting these data points on a graph, we can observe the distribution of concentrations over different distances. The resulting curve often takes on a Gaussian shape due to the underlying statistical properties involved.
Therefore, when referring to concentration vs distance plots, it is common for them to resemble the Gaussian distribution.