# What is a linear regression model?

**Linear regression**attempts to model the relationship between two variables by fitting a

**linear**equation to observed data. A

**linear regression**line has an equation of the form Y = a + bX, where X

**is the**explanatory variable and Y

**is the**dependent variable.

A.

### What is an appropriate linear model?

If the points in a residual plot are randomly dispersed around the horizontal axis, a

**linear regression model**is**appropriate**for the data; otherwise, a non-**linear model**is more**appropriate**. The first plot shows a random pattern, indicating a good fit for a**linear model**.#### Is it better to have a positive or negative residual?

If you**have a positive**value for**residual**, it means the actual value was MORE than the predicted value. The person actually did**better**than you predicted. Under the line, you OVER-predicted, so you**have**a**negative residual**. Above the line, you UNDER-predicted, so you**have a positive residual**.#### What is the residual value of my car?

3.**Residual**-**value**ruse. A critical factor in leasing a**car**is called the**residual value**— how much it will be**worth**when the lease ends. For instance, the lender may figure that a**car**selling for $20,000 today will be**worth**$10,000 three years from now, and will calculate monthly payments to cover that loss in**value**.#### Is residual value based on MSRP?

The**residual value**is shown as a dollar figure, but it's actually calculated as a percentage of**MSRP**(Manufacturer's**Suggested Retail Price**). For example, let's say the car you're**leasing**has a sticker**price**(**MSRP**) of $25,000 and its**residual value**is 50% after a 36 month**lease**.

B.

### What is meant by linear regression model?

In statistics,

**linear regression**is a**linear**approach to modelling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables). For more than one explanatory variable, the process is called multiple**linear regression**.#### What is a linear relationship?

**Linear relationships**can be expressed either in a graphical format where the variable and the constant are connected via a straight line or in a mathematical format where the independent variable is multiplied by the slope coefficient, added by a constant, which determines the dependent variable.#### What is a linear regression?

In statistics,**linear regression**is a**linear**approach to modelling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables). For more than one explanatory variable, the process is called multiple**linear regression**.#### What is the formula for linear regression?

You might also recognize the**equation**as the slope**formula**. The**equation**has the form Y=a+bX, where Y is the dependent variable (that's the variable that goes on the Y axis), X is the independent variable (i.e. it is plotted on the X axis), b is the slope of the line and a is the y-**intercept**.

C.

### What is the general linear model?

The

**general linear model**incorporates a number of different statistical**models**: ANOVA, ANCOVA, MANOVA, MANCOVA, ordinary**linear regression**, t-test and F-test. The**general linear model**is a generalization of multiple**linear regression model**to the case of more than one dependent variable.#### What is the definition of linear model?

In statistics, the term**linear model**is used in different ways according to the context. The most common occurrence is in connection with**regression models**and the term is often taken as synonymous with**linear regression model**. However, the term is also used in time series analysis with a different**meaning**.#### What is a multiple correlation coefficient?

In statistics, the coefficient of**multiple correlation**is a measure of how well a given variable can be predicted using a linear function of a set of other variables. It is the**correlation**between the variable's values and the best predictions that can be computed linearly from the predictive variables.#### What is the meaning of logit?

The**logit**(/ˈlo?d??t/ LOH-jit) function is the inverse of the sigmoidal "logistic" function or logistic transform used in mathematics, especially in statistics. When the function's variable represents a probability p, the**logit**function gives the log-odds, or the logarithm of the odds p/(1 − p).

Updated: 4th October 2019