The answer will depend on the context. If it is something like cab fare, a possible model is C = F + RD where F is the fixed cost that you pay for the cab hire, R is the Rate per unit of distance, and D is the distance measured in those units.
There are many variations. In some cases, the basic amount (F) includes some distance. In some cases F is dependent of the day of the week, time of day, number of passengers, number of suitcases.
The answer will depend on the context. If it is something like cab fare, a possible model is C = F + RD where F is the fixed cost that you pay for the cab hire, R is the Rate per unit of distance, and D is the distance measured in those units.
There are many variations. In some cases, the basic amount (F) includes some distance. In some cases F is dependent of the day of the week, time of day, number of passengers, number of suitcases.
The answer will depend on the context. If it is something like cab fare, a possible model is C = F + RD where F is the fixed cost that you pay for the cab hire, R is the Rate per unit of distance, and D is the distance measured in those units.
There are many variations. In some cases, the basic amount (F) includes some distance. In some cases F is dependent of the day of the week, time of day, number of passengers, number of suitcases.
The answer will depend on the context. If it is something like cab fare, a possible model is C = F + RD where F is the fixed cost that you pay for the cab hire, R is the Rate per unit of distance, and D is the distance measured in those units.
There are many variations. In some cases, the basic amount (F) includes some distance. In some cases F is dependent of the day of the week, time of day, number of passengers, number of suitcases.
The answer will depend on the context. If it is something like cab fare, a possible model is C = F + RD where F is the fixed cost that you pay for the cab hire, R is the Rate per unit of distance, and D is the distance measured in those units.
There are many variations. In some cases, the basic amount (F) includes some distance. In some cases F is dependent of the day of the week, time of day, number of passengers, number of suitcases.
LinearIn a linear model, the plotted data follows a straight line. Every data point may not fall on the line, but a line best approximates the overall shape of the data. You can describe every linear model with an equation of the following form:y = mx + bIn this equation, the letter "m" describes the angle, or "slope," of the line. The "x" describes any chosen value on the horizontal axis, while the "y" describes the number on the vertical axis that corresponds to the chosen "x" value.QuadraticIn a quadratic model, the data best fits a different type of curve that mathematicians call quadratic. Quadratic models have a curved shape that resembles the letter "u." You can describe all quadratic models with an equation of the form:Y = ax^2 + bx + cAs with linear models, the "x" corresponds to a chosen value on the horizontal axis and "y" gives the correlating value on the vertical axis. The letters "a," "b" and "c" represent any number, i.e., they will vary from equation to equation
PDEs are used in simulation of real life models like heat flow equation is used for the analysis of temperature distribution in a body, the wave equation for the motion of a waveforms, the flow equation for the fluid flow and Laplace’s equation for an electrostatic potential.
9d=m
idea model.
by using mathamatics, we can better understand the economic theories.mathamatical models, diffrensiation,linear programming these are very help full to make analysis of variabels
y=4x + 3 is an example for a linear equation just make sure that x is to the first power and you should be good
The objective function and the constraints.
Annette J. Dobson has written: 'An Introduction to Generalized Linear Models, Third Edition' 'An introduction to generalized linear models' -- subject(s): Linear models (Statistics) 'Introduction to statistical modelling' -- subject(s): Linear models (Statistics)
R. B. Bapat has written: 'Linear algebra and linear models' -- subject(s): Algebras, Linear, Linear Algebras, Linear models (Statistics), Multivariate analysis
Salomon Minkin has written: 'Assessing the quadratic approximation to the log-likelihood function in non-normal linear models'
Equation model?
LinearIn a linear model, the plotted data follows a straight line. Every data point may not fall on the line, but a line best approximates the overall shape of the data. You can describe every linear model with an equation of the following form:y = mx + bIn this equation, the letter "m" describes the angle, or "slope," of the line. The "x" describes any chosen value on the horizontal axis, while the "y" describes the number on the vertical axis that corresponds to the chosen "x" value.QuadraticIn a quadratic model, the data best fits a different type of curve that mathematicians call quadratic. Quadratic models have a curved shape that resembles the letter "u." You can describe all quadratic models with an equation of the form:Y = ax^2 + bx + cAs with linear models, the "x" corresponds to a chosen value on the horizontal axis and "y" gives the correlating value on the vertical axis. The letters "a," "b" and "c" represent any number, i.e., they will vary from equation to equation
Charles E. McCulloch has written: 'Generalized, linear, and mixed models' -- subject(s): Linear models (Statistics)
essential attributes of linear programming models and its uses
H. L. Koul has written: 'Weighted empiricals and linear models' -- subject(s): Autoregression (Statistics), Linear models (Statistics), Regression analysis, Sampling (Statistics) 'Weighted empirical processes in dynamic nonlinear models' -- subject(s): Autoregression (Statistics), Linear models (Statistics), Regression analysis, Sampling (Statistics)
linear interaction transactional
Roberto Sanchez Mariano has written: 'On distributions and moments of single-equation estimators in a set of simultaneous linear stochastic equations' -- subject(s): Mathematical models, Social sciences