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Suppose a revolutionary hypothesis has been proposed by a famous professor brainstorm, and if the truth be known, it really did not confirm to facts (population parameters). In the formal language of hypothesis testing, it is null hypothesis that is true, after all. (The professor interpreted his results in 5% level). His research was published and he won accolades for his scientific breakthrough.
What does this story say about hypothesis testing and research? What is the likelihood of this happening? There are number of safeguards in place so this should not happen in the scientific world what are some of these?
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This task mainly focus on the hypothesis testing procedure and the results carried out by professor Brainstrom. A discrete distribution is defined as the distribution in which the random variables take only the discrete values. A discrete random variable is a random variable that has countable values, such as a list of non-negative integers
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When formulating the conclusion to the test, why is the phrase fail to reject the null hypothesis more accurate than the phrase accept the null hypothesis?
A company is filling bags of rock salt to a level of 50 pounds. It believes that all bags are filled correctly, but would like to use a hypothesis test with an alpha of 0.05 to check this belief.
A random sample of 200 people was taken. Sixty percent of the people favor President Obama. The 95% confidence interval for the true population of people who favor Obama is?
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