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 followving sample data: 112.3 97.0 92.7 86.0 102.0 99.2 95.8 103.5 89.0 86.7 75.4 70.9 57.8 49.0 73.8 73.7 67.8 59.6 57.5 48.9 A USE SALT (a) Obtain the equation of the least squares line. (Round all numerical values to four decimal places.) y= Interpret the slope. O A one MPa decrease in cube strength is associated with an increase in the predicted axial strength equal to the slope. O A one MPa decrease in axial strength is associated with an increase in the predicted cube strength equal to the slope. O A one MPa increase in axial strength is associated vwith an increase in the predicted cube strength equal to the slope. O A one MPa increase in cube strength is associated with an increase in the predicted axcial strength equal to the slope. (b) Calculate the coefficient of determination. (Round your answer to four decimal places.) Interpret the coefficient of determination. O The coefficient of determination is the proportion of the observed variation in axcial strength of asphalt samples of this type that cannot be attributed to its linear relationship with cube strength. O The coefficient of determination is the number of the observed samples of axial strength of asphalt that cannot be explained by variation in cube strength. O The coefficient of determination is the proportion of the observed variation in axcial strength of asphalt samples of this type that can be attributed to its linear relationship with cube strength. O 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. (c) Calculate an estimate of the error standard deviation a in the simple linear regression model. (Round your answer to three decimal places.) MPa Interpret the estimate of the error standard deviation a in the simple linear regression model. O The model's prediction for axcial strength will typically differ from the specimen's actual axcial strength by an amount greater than one error standard deviation. O The model's prediction for acial strength will typically differ from the specimen's actual axcial strength by an amount within one error standard deviation. O The model's prediction for axial strength will typically differ from the specimen's actual axial strength by an amount greater than two error standard deviations. The model's prediction for avial strenath will tvnicaly differ from the s rennth an amount within standard
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
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