In: Statistics and Probability
True or False
1. Hypothesis tests are robust to the significance level you choose, meaning regardless of the alpha level: .10, .05, or .01, our test will have the same conclusion or result.
2. If alpha is greater than the p-value, then we reject the null hypothesis.
3. The p-value is strictly the probability the null hypothesis being true.
4. Hypothesis tests are accessing the evidence provided by the data and deciding between two competing hypotheses about the population parameter.
5. When the alternative hypothesis is saying that the parameter is different than the hypothesized value, we have a two-sided test.