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Refer to the SENIC data set in Appendix C.1. Length of stay (Y) is to be predicted, and the pool of potential predictor variables includes all other variables in the data set except medical school affiliation and region. It is believed that a model with logio Y as the response variable and the predictor variables in first-order terms with no interaction terms will be appropriate. Consider cases 57–113 to constitute the model-building data set to be used for the following analyses. a Prepare separate dot plots for each of the predictor variables. Are there any noteworthy features in these plots? Comment b. Obtain the scatter plot matrix. Also obtain the correlation matrix of the X varjables. Is there evidence of strong linear pairwise associations among the predictor variables here? c. Obtain the three best subsets according to the Cp criterion, Which of these subset models appears to have the smallest bias?

Sagot :

We make distinct dot plots for every predictor variable.

x₂=6.3368+0.7604×x₄

x₂=6.67+0.04×x₆

x₂=7.718+0.04×x₁₂

Given that,

Refer to Appendix C.1's SENIC data collection. All additional variables in the data set, with the exception of medical school affiliation and area, are included in the list of potential predictor variables for length of stay (Y). It is anticipated that the best model will have logio Y as the response variable, first-order terms for the predictor variables, and no interaction terms. Take examples 57–113 into consideration as the model-building data set for the subsequent studies.

We have to make distinct dot plots for every predictor variable. Do these storylines have any significant elements.

We know that,

Average length of stay = x₂

Infection risk = x₄

X-ray ratio = x₆

Available Services = x₁₂

57–113 into consideration as the model-building data set for the subsequent studies.

By using, regression equation for x₂ as dependent variable and regression equation for x₄ as independent variable..

Then,

x₂=6.3368+0.7604×x₄

x₂=6.67+0.04×x₆

x₂=7.718+0.04×x₁₂

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