Question

When studying the relationship between hours spent on a computer and vision loss, the researchers have a significant R-squared. They then add a second independent variable of sun exposure. The R-squared in the model that includes both independent variables is significant, but the R-squared change is not. You know this means: \text{having both variables in the model explains significantly more variation in vision loss.} \text{sun exposure may not be significant and should be examined further.} \text{because the model is significant both variables should be included.} \text{the R-squared change only matters with the hours spent on the computer.}

          When studying the relationship between hours spent on a computer and vision loss, the researchers have a significant R-squared. They then add a second independent variable of sun exposure. The R-squared in the model that includes both independent variables is significant, but the R-squared change is not. You know this means:

\text{having both variables in the model explains significantly more variation in vision loss.}

\text{sun exposure may not be significant and should be examined further.}

\text{because the model is significant both variables should be included.}

\text{the R-squared change only matters with the hours spent on the computer.}

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When studying the relationship between hours spent on a computer and vision loss, the researchers have a significant R-squared. They then add a second independent variable of sun exposure. The R-squared in the model that includes both independent variables is significant, but the R-squared change is not. You know this means:

having both variables in the model explains significantly more variation in vision loss.

sun exposure may not be significant and should be examined further.

because the model is significant both variables should be included.

the R-squared change only matters with the hours spent on the computer.

Added by Stephen R.

Elementary Statistics a Step by Step Approach

Allan G. Bluman 9th Edition

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Solved by Expert Joanna Quigley

01/30/2024

Step 1

Step 1: The fact that the R-squared in the model that includes both independent variables is significant means that the overall model with both variables is explaining a significant amount of the variation in vision loss. Show more…

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squared in the model that includes both independent variables is significant, but the R-squared change is not. You know this means: having both variables in the model explains significantly more variation in vision loss. sun exposure may not be significant and should be examined further. because the model is significant both variables should be included. the R-squared change only matters with the hours spent on the computer. When studying the relationship between hours spent on a computer and vision loss, the researchers have a significant R-squared. They then add a second independent variable of sun exposure. The R- squared in the model that includes both independent variables is significant, but the R-squared change is not. You know this means: O having both variables in the model explains significantly more variation in vision loss. O sun exposure may not be significant and should be examined further. O because the model is significant both variables should be included O the R-squared change only matters with the hours spent on the computer.

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