Final answer:
The percentage of the variation in the time to completion explained by the variation in temperature is 19%. A hypothesis test can be conducted to determine if a linear regression model is a good fit for the data and can be used for prediction.
Step-by-step explanation:
The percentage of the variation in the time to completion explained by the variation in the temperature can be determined using the coefficient of determination, which is equal to the square of the correlation coefficient. If the correlation coefficient is 0.44, then the coefficient of determination is 0.44^2 = 0.1936, which is equal to 19.36%.
Therefore, 19% of the variation in the time to completion can be explained by the variation in temperature.
To determine if a linear regression model is a good fit for the data and can be used for prediction, a hypothesis test can be conducted. This test compares the observed data to the predicted values from the regression model.
If the predicted values closely match the observed data, then the linear regression model is a good fit and can be used for prediction.
On the other hand, if there is a significant difference between the predicted and observed values, then the linear regression model would not be a good fit for prediction.