temperature was used to predict the growth rate of sod on the sod farm. a least - squares regression line…

temperature was used to predict the growth rate of sod on the sod farm. a least - squares regression line was fit to the data. it was found that the coefficient of determination was 0.78. what does that tell us?\n78% of the variation in the growth rate of the sod is explained by the linear relationship with temperature.\na rise of 1 degree in temperature causes a 78% growth rate in the sod.\n78% of the time, there is a linear relationship between temperature and the growth rate of the sod.\n78% of the variation in temperature is explained by the linear relationship with the growth rate of the sod.

temperature was used to predict the growth rate of sod on the sod farm. a least - squares regression line was fit to the data. it was found that the coefficient of determination was 0.78. what does that tell us?\n78% of the variation in the growth rate of the sod is explained by the linear relationship with temperature.\na rise of 1 degree in temperature causes a 78% growth rate in the sod.\n78% of the time, there is a linear relationship between temperature and the growth rate of the sod.\n78% of the variation in temperature is explained by the linear relationship with the growth rate of the sod.

Answer

Brief Explanations:

The coefficient of determination ($R^{2}$) measures the proportion of the variance in the dependent - variable (here, the growth rate of sod) that is predictable from the independent variable (temperature). A value of $R^{2}=0.78$ means that 78% of the variation in the growth rate of the sod can be accounted for by its linear relationship with temperature.

Answer:

78% of the variation in the growth rate of the sod is explained by the linear relationship with temperature.