Will Underwood

2022-09-14

For a data set of weights and highway fuel consumption amounts of four types of automobile, the linear correlation coefficient is found and the P-value is 0.001. Please, write a statement that interprets the P-value and includes a conclusion about linear correlation.

acorazarxf

The P-value indicates that the probability of a linear correlation coefficient that is at least as extreme is 0.1% which is low so there is sufficient evidence to conclude that there is a linear correlation between weight and highway fuel consumption in automobiles.

Janet Hart

Null hypothesis: There is no linear correlation between the two variables.
Alternative hypothesis: There is linear correlation between the two variables.
The P-value is 0.001.
Decision rule: if $P-value<\alpha$ , then reject the null hypothesis. Otherwise, do not reject the null hypothesis.
Consider the level of significance as 0.01.
Thus, the P-value (0.001) is less than the level of significance (0.01).
Based on decision rule, reject the null hypothesis.

Thus, there is sufficient evidence to conclude that there is a linear correlation between weight and highway fuel consumption in automobiles.

The P-value indicates that the probability of a linear correlation coefficient that is at least as extreme is 0.1% which is low so there is sufficient evidence to conclude that there is a linear correlation between weight and highway fuel consumption in automobiles.

Do you have a similar question?