Answer:
In this case, a sample was taken and an hypothesis test was done. The P-value of the test is 0.0016.
a) With this P-value, the null hypothesis will be rejected. That means it will be considered false with statistical evidence.
If the null hypothesis is true, and it is rejected, we will have what is called a Type I error (rejecting the null hypothesis when it is true).
The probability of this error depends from the significance level (the higher the significance level, the higher the probability of a Type I error).
b) This P-value is obviously smaller than any significance level. That means that the effect is statistically significant and there is evidence to reject the null hypothesis, whatever it was.
Step-by-step explanation:
