Question

I need a 250 word original response to the following prompt:

"Discuss the statistics that must be evaluated when reviewing the regression analysis output. Provide examples of what the values represent and an explanation of why they are important."

Answer 1

A relapse investigation says whether the anticipated variable changes with the needy variable . In relapse the investigation in every case direct to the assessment of the R square , F test translation of beta variable lastly the relapse condition

At the point when the relapse is led a F worth and importance level of F esteem is determined if the F esteem is measurably noteworthy the model clarifies a lot of difference in the result variable . Routinely the worth is noteworthy when p<0.05 .Like this a R2 esteem is additionally determined it very well may be shown as the percent of fluctuation in the result variable that is clarified by an anticipated variable . After these it is imperative to acquire the beta variable it very well may be negative or positive and have a t esteem . The beta variable is the level of progress of result variable for each 1 unit of progress in forecast factors If beta coefficient is negative then every 1 unit increment in the expectation variable the result variable will diminish by the beta worth . Additionally on the off chance that the beta coefficient is certain, at that point each 1 unit increment in the forecast variable the result variable will increment by the beta coefficient esteem .

The P esteem for each term tests the invalid speculation that the coefficient is zero methods no impact , a low P esteem demonstrate that you can dismiss the invalid theory ,the P esteem give u a thought regarding which terms to keep in the relapse model .R squared says how close the information are to the fitted relapse line . On the off chance that we get 0 % it says that model clarify none of the changeability of the reaction information around it's mean.

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