# For the past decade, rubber powder has been used in asphalt cement to improve performance. An article includes a regression of y = axial strength (MPa) on x cube strength (MPa)based on the following sample data:112.3 97.0 92.7 86.0 102.0 99.2 95.8 103.5 89.0 86.774.7 70.7 58.0 49.2 74.3 73.0 68.3 59.5 57.3 48.9(a) Obtain the equation of the least squares line. (Round all numerical values to four decimal places.)%3DInterpret the slope.A one MPa decrease in axial strength is associated with an increase in the predicted cube strength equal to the slope.A one MPa decrease in cube strength is associated with an increase in the predicted axial strength equal to the slope.A one MPa increase in axial strength is associated with an increase in the predicted cube strength equal to the slope.A one MPa increase in cube strength is associated with an increase in the predicted axial strength equal to the slope.(b) Calculate the coefficient of determination. (Round your answer to four decimal places.)Interpret the coefficient of determination.The coefficient of determination is the proportion of the observed variation in axial strength of asphalt samples of this type that can be attributed to its linear relationshipwith cube strength.The coefficient of determination is the number of the observed samples of axial strength of asphalt that can be explained by variation in cube strength.The coefficient of determination is the proportion of the observed variation in axial strength of asphalt samples of this type that cannot be attributed to its linearrelationship with cube strength.The coefficient of determination is the pumber of the observed samples of axial strenath of asohalt that cannot be explained by vadiationMy Questions...renoth#DA0 ENG 917 PMSkypeChapter 12 - .e certified.pdf-TOSHIBAYGURENDWOME

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Step 1

a)Regression:

In order to obtain the least square regression line, first perform regression analysis on the data.

The regression analysis is conducted here by using EXCEL. The software procedure is given below:

• Enter the data.
• Select Data > Data Analysis > Regression> OK.
• Enter Input Y Range as \$B...

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