The Simple Regression Model

Statistics
Tutor: None Selected Time limit: 1 Day

What terms describe the fit of a regression equation to the data? When is this fit good enough?

Aug 18th, 2015

Thank you for the opportunity to help you with your question!

 

 When its good enough it implies that

- The model describes the data adequately .Its a prerequisite that you will trust the the conclusion. its evaluated by using a graph or  scatters and plots

-  When its tested that the  the relationships  you modeled depends on the  model parameters

will continue. Be patient please

Please let me know if you need any clarification. I'm always happy to answer your questions.
Aug 18th, 2015

Regression Fitness  describes how  well it fits  a set of  observation  . Measures  the fitness  by summarizing

 Te the b discrepancy of the observed values i n the data provided .

Terms used to refer are

 1. Test for residual

2. Normality test

3. Fit of distribution




Aug 18th, 2015

Regression Fitness  describes how  well it fits  a set of  observation  . Measures  the fitness  by summarizing

 Te the b discrepancy of the observed values i n the data provided .

Terms used to refer are

 1. Test for residual

2. Normality test

3. Fit of distribution




Aug 18th, 2015

Regression Fitness  describes how  well it fits  a set of  observation  . Measures  the fitness  by summarizing

 Te the b discrepancy of the observed values i n the data provided .

Terms used to refer are

 1. Test for residual

2. Normality test

3. Fit of distribution




Aug 18th, 2015

Yes I need clarification please. Not understanding the answer or the spelling. 

Aug 18th, 2015

I am sorry for that , just a minute and i will clarify

Aug 18th, 2015

.The goodness of fit of a  statistical model describes how well it fits a set of observations. Measures of goodness of fit typically summarize the discrepancy between observed values and the values expected under the model in question. Such measures can be used in statistical hypothesis model , e.g.  test of normality .

Regression Fitness  describes how  well it fits  a set of  observation  . Measures  the fitness  by summarizing the following test which are very important in determining the fitness of the data.

 1. Test for residual

2. Normality test

3. Fit of distribution

 The following are conditions/terms .

-A well-fitting regression model results in predicted values close to the observed data values.- 

- When P>a

-Adequately describe the functional relationship between the experimental factors and the response variable.

 Hope your understanding now. Thanks

Aug 18th, 2015

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Aug 18th, 2015
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Aug 18th, 2015
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