The p-value of a one-sided hypothesis test is 0.056. At the 10% significance level, what can we conclude if it was a two-sided hypothesis test instead?

In a two-sided hypothesis test, the p-value would be doubled. This is because we are testing for the possibility of the relationship in both directions. So, the p-value would be 0.056 * 2 = 0.112.

The significance level is the probability of rejecting the null hypothesis if it is true. In this case, the significance level is 10% or 0.10.

Comparing the p-value (0.112) with the significance level (0.10), we see that the p-value is greater than the significance level.

Therefore, we fail to reject the null hypothesis at the 10% significance level in a two-sided hypothesis test. This means that we do not have enough evidence to conclude that the alternative hypothesis is true.