1.The correct answers are ：
A correlation coefficient numerically close to 1 and A large sample is used to calculate the regression equation
A correlation coefficient numerically close to 1 and a large sample is used to calculate the regression equation and increase the reliability of forecasting.
A correlation coefficient close to +1 or-1 indicates a strong linear relationship between X and Y.
The regression equation is therefore more reliable for forecasting.
Working to a high number of decimal places gives spurious accuracy unless both the data itself is accurate to the same degree and the methods used lend themselves to such precision.
Forecasting for values of X outside the range of the original data leads to unreliable estimates, because there is no evidence that the same regression relationships hold for such values.
The regression equation is worthless unless a sufficiently large sample was used to calculate it. In practice, samples of about ten or more are acceptable.
2.The correct answers are ：
There is a strong relationship between the level of car ownership and the number of road deaths and 53% of the variation in the level of road deaths from one country to the next can be explained by the corresponding variation in the level of car ownership
High levels of correlation do not prove that there is cause and effect.
A correlation coefficient of 0.73 would generally be regarded as indicating a strong linear
relationship between the variables.
The coefficient of determination provides this information and is given by squaring the correlation coefficient, resulting in 53% in this case.
The coefficient of determination provides this information and not the correlation coefficient.
Remember that you must square the correlation coefficient in order to obtain the coefficient of determination.
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