Without seeing the specific polynomial division you performed, it is difficult to say whether it was done correctly. However, when dividing a polynomial by linear factors, it is important to ensure that the division is carried out systematically, with attention to each step of the process. It is also important to double-check your work to ensure that no mistakes were made. If you are unsure about the correctness of your polynomial division, it may be helpful to seek assistance from a teacher or tutor. **

The relationship between the variables is non-linear. **

A linear charge distribution along a circular arc refers to a scenario where electric charge is uniformly distributed along a curved path in a circular shape. This distribution can be seen in situations where there is a wire or object following a circular path and charge is spread out along its length. The charge density remains constant along the arc, and this distribution can be used to calculate the electric field at various points around the circular arc using techniques from calculus and electromagnetism. **

A linear charge distribution on a circular arc refers to a situation where electric charge is distributed along a curved path in a linear manner. This means that the charge density is constant along the arc, resulting in a uniform distribution of charge. The arc can be part of a complete circle or a segment of a larger curve, and the charge can be positive or negative. This type of distribution is commonly encountered in problems involving the calculation of electric fields and potentials due to curved geometries. **

The question about the Poisson distribution and linear transformation is about how to find the distribution of a linear transformation of a Poisson random variable. In other words, if we have a Poisson random variable X with parameter λ, and we want to find the distribution of Y = aX + b for some constants a and b, how can we determine the distribution of Y? This question is important in understanding how to manipulate and transform Poisson random variables in statistical and probabilistic applications. **

Polynomial division without the last coefficient for the linear factor involves dividing a polynomial by a linear factor without considering the constant term of the linear factor. This means that the division is done as if the linear factor had a coefficient of 1. The process is similar to regular polynomial division, but the final result will be missing the constant term that would normally be present in the quotient. This type of division is useful in simplifying expressions or solving equations where the constant term of the linear factor is not relevant. **

A linear term is a single variable or constant raised to the power of 1, such as 3x or 5. A linear equation is an equation that can be written in the form y = mx + b, where x is the independent variable, y is the dependent variable, m is the slope, and b is the y-intercept. A linear function is a mathematical relationship between two variables that can be represented by a straight line on a graph, and it can be expressed in the form f(x) = mx + b, where f(x) represents the dependent variable, x is the independent variable, m is the slope, and b is the y-intercept. **

The linear span of a linear space is the set of all possible linear combinations of the vectors in that space. In other words, it is the collection of all possible vectors that can be obtained by scaling and adding the vectors in the space. The linear span forms a subspace of the original space and is often used to describe the "space" that is covered by the original set of vectors. It is a fundamental concept in linear algebra and is used to understand the properties and structure of vector spaces. **