When the alpha level is set at .05, this means that: there is a 5 percent chance of accepting a true null hypothesis there is a 5 percent chance of rejecting a true null hypothesis there is a 10 percent chance of rejecting a false null hypothesis there is a 5 percent chance of accepting a false alternative hypothesis

What does it mean if a researcher sets his/her alpha at say .01, and rejects the null hypothesis? How does this differ from setting the alpha at .05 and rejecting the null? In which case is the researcher going to be most likely to reject the null hypothesis?

95 % level of significance means there are _____ of 100 chances of acceptance and 5 % chances of errora.95b.5c.9.5d.0.95

(iv) Make a decision and conclusion for the hypothesis test in context. Use a significance level of 5% (α = 0.05).

What is the difference between setting the alpha value equal to 0.05 and the alpha value equal to 0.01 in hypothesis tests?a.with α=0.05, one is less willing to risk type I error.b.with α=0.05, one is more willing to risk type I error.c.with α=0.05, one is more willing to risk type II error.d.α=0.05 or α=0.01 is generally decided as the last step in hypothesis test depending upon the test result.

he p-value for the hypothesis test is 0.0139 , which means the observed difference is/ is noy statistically significant at the 5% level