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Q: How is a linear model appropriate?
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What is a linear model?

A model in which your mother.


What is the purpose of a residual analysis in simple linear regression?

One of the main reasons for doing so is to check that the assumptions of the errors being independent and identically distributed is true. If that is not the case then the simple linear regression is not an appropriate model.


How would you interpret the findings of a correlation study that reported a linear correlation coefficient of 1.67?

There is not enough information to say much. To start with, the correlation may not be significant. Furthermore, a linear relationship may not be an appropriate model. If you assume that a linear model is appropriate and if you assume that there is evidence to indicate that the correlation is significant (by this time you might as well assume anything you want!) then you could say that the dependent variable increases by 1.67 for every unit change in the independent variable - within the range of the independent variable.


How would you interpret the findings of a correlation study that reported a linear correlation coefficient of -0.13?

There is not enough information to say much. To start with, the correlation may not be significant. Furthermore, a linear relationship may not be an appropriate model. If you assume that a linear model is appropriate and if you assume that there is evidence to indicate that the correlation is significant (by this time you might as well assume anything you want!) then you could say that the dependent variable decreases by 0.13 units for every unit change in the independent variable - within the range of the independent variable.


What is The model y A plus Bx is a?

It is a linear model.


What do you know about a linear model from the correlation coefficient?

It's a measure of how well a simple linear model accounts for observed variation.


Why is it helpful to use a linear model for a set of data?

when does it make sense to choose a linear function to model a set of data


How can you graph linear and parabolic rules with an appropriate scale?

Yes.


What is modeling linear?

A model in which your mother.


What is linear mathematical model?

Calculus


What is the normal probability plot of residuals?

When you use linear regression to model the data, there will typically be some amount of error between the predicted value as calculated from your model, and each data point. These differences are called "residuals". If those residuals appear to be essentially random noise (i.e. they resemble a normal (a.k.a. "Gaussian") distribution), then that offers support that your linear model is a good one for the data. However, if your errors are not normally distributed, then they are likely correlated in some way which indicates that your model is not adequately taking into consideration some factor in your data. It could mean that your data is non-linear and that linear regression is not the appropriate modeling technique.


Do linear relationships show the same slope between any two points on a line?

Depends on your definition of "linear" For someone taking basic math - algebra, trigonometry, etc - yes. Linear means "on the same line." For a statistician/econometrician? No. "Linear" has nothing to do with lines. A "linear" model means that the terms of the model are additive. The "general linear model" has a probability density as a solution set, not a line...