0
y^2 X y^3 = y^(2 + 3) = y^5
You can only do this if the coefficient 'y' is the same for both terms.
Remember
y^2 = y X y
y^3 = y X y X y
Hence
y^2 X y^3 = y X y X y X y X y = y^5
Similarly for division/subtraction
y^3 / y^2 = y^(3 - 2 ) = y^1 = y The power of '1' is trivial and not normally shown.
NB You CANNOT do z^2 X y^3 by adding the indices.
z^2 X y^3 is (z^2)*(y^3)
Still curious? Ask our experts.
Chat with our AI personalities
Coach
Jordan
Rene
Add your answer:
Earn +20 pts
What is 2xy?
In mathematics, the expression 2xy represents the product of the number 2 and the variables x and y. This expression is known as a monomial, specifically a binomial because it consists of two terms. When simplified, 2xy cannot be further reduced unless additional information about the variables x and y is provided.
The regression equation is determined by minimizing?
The total squared error between the predicted y values and the actual y values
Is area cubed or squared?
Area is squared. In mathematics, area is a two-dimensional measurement of the size of a shape, typically measured in square units (such as square meters or square feet). The formula for calculating the area of a shape involves multiplying two linear dimensions (such as length and width), resulting in a value with units squared. Cubing a linear dimension would result in a measurement of volume, not area.
What is 64 cube?
The cubed root of 64 is 4. 4*4*4=64.
How do you calculate mean squared error?
The Mean Squared Error (MSE) is a measure of how close a fitted line is to data points. For every data point, you take the distance vertically from the point to the corresponding y value on the curve fit, this is known as the error, and square the value. Next you add up all those values for all data points, and divide by the number of points. The reason for squaring is so negative values do not cancel positive values. The smaller the Mean Squared Error, the closer the fit is to the data. The MSE has the units squared of whatever is plotted on the vertical axis.
