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In: Statistics and Probability

It is possible to compare multiple means with a single set of hypotheses (one null and...

  1. It is possible to compare multiple means with a single set of hypotheses (one null and one alternate hypothesis).   
  2. In hypothesis testing, the goal is to accept the null hypothesis.

  1. Point estimates are known for estimating the population values perfectly.
  2. In hypothesis testing, the region(s) of rejection is always in the tail(s).
  3. If the confidence level is changed from 90% to 95%, the confidence interval values would get closer to each other.

True or false? with explanations?

Solutions

Expert Solution

  1. It is possible to compare multiple means with a single set of hypotheses (one null and one alternate hypothesis).   - True. Anova test is an example which compare multiple means with a single set of hypotheses.
  2. In hypothesis testing, the goal is to accept the null hypothesis. - False - the goal is to reject the null hypothesis.
  3. Point estimates are known for estimating the population values perfectly. - False, point estimates are know for estimating the population values with a margin of error.
  4. In hypothesis testing, the region(s) of rejection is always in the tail(s). - True - we reject the null hypothesis when there is low probability of finding the observed, or more extreme, results when the null hypothesis is true
  5. If the confidence level is changed from 90% to 95%, the confidence interval values would get closer to each other. - False. Increasing the confidence level, will increase the critical z value which will increase the margin of error and length of confidence interval. In that case, the confidence interval values would get farther from each other.

orchestra answered 1 year ago
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