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  2. Simple linear regression - Wikipedia

    en.wikipedia.org/wiki/Simple_linear_regression

    The above equations are efficient to use if the mean of the x and y variables (¯ ¯) are known. If the means are not known at the time of calculation, it may be more efficient to use the expanded version of the α ^ and β ^ {\displaystyle {\widehat {\alpha }}{\text{ and }}{\widehat {\beta }}} equations.

  3. Equation - Wikipedia

    en.wikipedia.org/wiki/Equation

    When there is only one variable, polynomial equations have the form P(x) = 0, where P is a polynomial, and linear equations have the form ax + b = 0, where a and b are parameters. To solve equations from either family, one uses algorithmic or geometric techniques that originate from linear algebra or mathematical analysis.

  4. Equation solving - Wikipedia

    en.wikipedia.org/wiki/Equation_solving

    In the simple case of a function of one variable, say, h(x), we can solve an equation of the form h(x) = c for some constant c by considering what is known as the inverse function of h. Given a function h : A → B , the inverse function, denoted h −1 and defined as h −1 : B → A , is a function such that

  5. Linear equation - Wikipedia

    en.wikipedia.org/wiki/Linear_equation

    The phrase "linear equation" takes its origin in this correspondence between lines and equations: a linear equation in two variables is an equation whose solutions form a line. If b ≠ 0 , the line is the graph of the function of x that has been defined in the preceding section.

  6. Elementary algebra - Wikipedia

    en.wikipedia.org/wiki/Elementary_algebra

    To solve this kind of equation, the technique is add, subtract, multiply, or divide both sides of the equation by the same number in order to isolate the variable on one side of the equation. Once the variable is isolated, the other side of the equation is the value of the variable. [37] This problem and its solution are as follows: Solving for x

  7. Linear regression - Wikipedia

    en.wikipedia.org/wiki/Linear_regression

    In statistics, linear regression is a model that estimates the linear relationship between a scalar response (dependent variable) and one or more explanatory variables (regressor or independent variable). A model with exactly one explanatory variable is a simple linear regression; a model with two or more explanatory variables is a multiple ...

  8. Function of a real variable - Wikipedia

    en.wikipedia.org/wiki/Function_of_a_real_variable

    A real-valued function of a real variable is a function that takes as input a real number, commonly represented by the variable x, for producing another real number, the value of the function, commonly denoted f(x). For simplicity, in this article a real-valued function of a real variable will be simply called a function. To avoid any ambiguity ...

  9. Cubic equation - Wikipedia

    en.wikipedia.org/wiki/Cubic_equation

    The characteristic equation of a third-order constant coefficients or Cauchy–Euler (equidimensional variable coefficients) linear differential equation or difference equation is a cubic equation. Intersection points of cubic Bézier curve and straight line can be computed using direct cubic equation representing Bézier curve.

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